Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\\n\\n
We wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
IntechOpen is proud to announce that 191 of our authors have made the Clarivate™ Highly Cited Researchers List for 2020, ranking them among the top 1% most-cited.
\n\n
Throughout the years, the list has named a total of 261 IntechOpen authors as Highly Cited. Of those researchers, 69 have been featured on the list multiple times.
\n\n\n\n
Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\n\n
We wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
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1. Introduction
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The main objective on the active vibration control problem of vehicles suspension systems is to get security and comfort for the passengers by reducing to zero the vertical acceleration of the body of the vehicle. An actuator incorporated to the suspension system applies the control forces to the vehicle body of the automobile for reducing its vertical acceleration in active or semi-active way.
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The topic of active vehicle suspension control system has been quite challenging over the years. Some research works in this area propose control strategies like LQR in combination with nonlinear backstepping control techniques (Liu et al., 2006) which require information of the state vector (vertical positions and speeds of the tire and car body). A reduced order controller is proposed in (Yousefi et al., 2006) to decrease the implementation costs without sacrificing the security and the comfort by using accelerometers for measurements of the vertical movement of the tire and car body. In (Tahboub, 2005), a controller of variable gain that considers the nonlinear dynamics of the suspension system is proposed. It requires measurements of the vertical position of the car body and the tire, and the estimation of other states and of the profile of the ride.
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This chapter proposes a control design approach for active vehicle suspension systems using electromagnetic or hydraulic actuators based on the Generalized Proportional Integral (GPI) control design methodology, sliding modes and differential flatness, which only requires vertical displacement measurements of the vehicle body and the tire. The profile of the ride is considered as an unknown disturbance that cannot be measured. The main idea is the use of integral reconstruction of the non-measurable state variables instead of state observers. This approach is quite robust against parameter uncertainties and exogenous perturbations. Simulation results obtained from Matlab are included to show the dynamic performance and robustness of the proposed active control schemes for vehicles suspension systems.
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GPI control for the regulation and trajectory tracking tasks on time invariant linear systems was introduced by Fliess and co-workers in (Fliess et al., 2002). The main objective is to avoid the explicit use of state observers. The integral reconstruction of the state variables is carried out by means of elementary algebraic manipulations of the system model along with suitable invocation of the system model observability property. The purpose of integral reconstructors is to get expressions for the unmeasured states in terms of inputs, outputs, and sums of a finite number of iterated integrals of the measured variables. In essence, constant errors and iterated integrals of such constant errors are allowed on these reconstructors. The current states thus differ from the integrally reconstructed states in time polynomial functions of finite order, with unknown coefficients related to the neglected, unknown, initial conditions. The use of these integral reconstructors in the synthesis of a model-based computed stabilizing state feedback controller needs suitable counteracting the effects of the implicit time polynomial errors. The destabilizing effects of the state estimation errors can be compensated by additively complementing a pure state feedback controller with a linear combination of a sufficient number of iterated integrals of the output tracking error, or output stabilization error. The closed loop stability is guaranteed by a simple characteristic polynomial assignment to the higher order compensated controllable and observable input-output dynamics. Experimental results of the GPI control obtained in a platform of a rotational mechanical system with one and two degrees of freedom are presented in (Chávez-Conde et al., 2006). Sliding mode control of a differentially flat system of two degrees of freedom, with vibration attenuation, is shown in (Enríquez-Zárate et al., 2000). Simulation results of GPI and sliding mode control techniques for absorption of vibrations of a vibrating mechanical system of two degrees of freedom were presented in (Beltrán-Carbajal et al., 2003).
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This chapter is organized as follows: Section 2 presents the linear mathematical models of suspension systems of a quarter car. The design of the controllers for the active suspension systems are introduced in Sections 3 and 4. Section 5 divulges the use of sensors for measuring the variables required by the controller while the simulation results are shown in Section 6. Finally, conclusions are brought out in Section 7.
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2. Quarter-car suspension systems
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2.1. Mathematical model of passive suspension system
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A schematic diagram of a quarter-vehicle suspension system is shown in Fig. 1(a). The mathematical model of passive suspension system is described by
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Figure 1.
Quarter-car suspension systems: (a) Passive Suspension System, (b) Active Electromagnetic Suspension System and (c) Active Hydraulic Suspension System.
where\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tm\n\t\t\t\t\t\t\t\t\ts\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\trepresents the sprung mass, \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tm\n\t\t\t\t\t\t\t\t\tu\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\tdenotes the unsprung mass, \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tc\n\t\t\t\t\t\t\t\t\ts\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\tis the damper coefficient of suspension, \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tk\n\t\t\t\t\t\t\t\t\ts\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\tand \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tk\n\t\t\t\t\t\t\t\t\tt\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t are the spring coefficients of suspension and the tire, respectively, \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tz\n\t\t\t\t\t\t\t\t\ts\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\tis the displacements of the sprung mass, \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tz\n\t\t\t\t\t\t\t\t\tu\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\tis the displacements of the unsprung mass and \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tz\n\t\t\t\t\t\t\t\t\tr\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t is the terrain input disturbance.
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2.2. Mathematical model of active electromagnetic suspension system
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A schematic diagram of a quarter-car active electromagnetic suspension system is illustrated in Fig.1 (b). The electromagnetic actuator replaces the damper, forming a suspension with the spring (Martins et al., 2006). The friction force of an electromagnetic actuator is neglected. The mathematical model of electromagnetic active suspension system is given by
where\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tm\n\t\t\t\t\t\t\t\t\ts\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t, \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tm\n\t\t\t\t\t\t\t\t\tu\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t, \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tk\n\t\t\t\t\t\t\t\t\ts\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t, \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tk\n\t\t\t\t\t\t\t\t\tt\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t, \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tz\n\t\t\t\t\t\t\t\t\ts\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t, \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tz\n\t\t\t\t\t\t\t\t\tu\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\tand \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tz\n\t\t\t\t\t\t\t\t\tr\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t represent the same parameters and variables as ones described for the passive suspension system. The electromagnetic actuator force is represented here by\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tF\n\t\t\t\t\t\t\t\t\tA\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t, which is considered as the control input.
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2.3. Mathematical model of hydraulic active suspension system
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\n\t\t\t\t\tFig. 1(c) shows a schematic diagram of a quarter-car active hydraulic suspension system. The mathematical model of this active suspension system is given by
where\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tm\n\t\t\t\t\t\t\t\t\ts\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t, \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tm\n\t\t\t\t\t\t\t\t\tu\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t, \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tk\n\t\t\t\t\t\t\t\t\ts\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t, \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tk\n\t\t\t\t\t\t\t\t\tt\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t, \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tz\n\t\t\t\t\t\t\t\t\ts\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t, \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tz\n\t\t\t\t\t\t\t\t\tu\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\tand \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tz\n\t\t\t\t\t\t\t\t\tr\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t represent the same parameters and variables shown for the passive suspension system. The hydraulic actuator force is represented by\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tF\n\t\t\t\t\t\t\t\t\tA\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t, while \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tF\n\t\t\t\t\t\t\t\t\tf\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t represents the friction force generated by the seals of the piston with the cylinder wall inside the actuator. This friction force has a significant magnitude \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t(\n\t\t\t\t\t\t\t\t\t200\n\t\t\t\t\t\t\t\tN\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t)\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t and cannot be ignored (Martins et al., 2006; Yousefi et al., 2006). The net force given by the actuator is the difference between the hydraulic force \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tF\n\t\t\t\t\t\t\t\t\tA\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t and the friction force\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tF\n\t\t\t\t\t\t\t\t\tf\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t.
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3. Control of electromagnetic suspension system
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The mathematical model of the active electromagnetic suspension system, illustrated in Fig. 1(b) is given by the equations (3) and (4). Defining the state variables\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tx\n\t\t\t\t\t\t\t\t1\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t=\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tz\n\t\t\t\t\t\t\t\ts\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t, \n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tx\n\t\t\t\t\t\t\t\t2\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t=\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tz\n\t\t\t\t\t\t\t\t\t˙\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\ts\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t, \n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tx\n\t\t\t\t\t\t\t\t3\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t=\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tz\n\t\t\t\t\t\t\t\tu\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\tand\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tx\n\t\t\t\t\t\t\t\t4\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t=\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tz\n\t\t\t\t\t\t\t\t\t˙\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tu\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t, the representation in the state-space is,
The force provided by the electromagnetic actuator as the control input is\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tu\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t=\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tF\n\t\t\t\t\t\t\t\tA\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t.
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The system is controllable with controllability matrix,
For simplicity, in the analysis of the differential flatness for the suspension system we have assumed that\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tk\n\t\t\t\t\t\t\t\tt\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tz\n\t\t\t\t\t\t\t\tr\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t=0\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t. In order to show the differential parameterization of all the state variables and control input, we first formulate the time derivatives up to fourth order for\n\t\t\t\t\t\n\t\t\t\t\t\tF\n\t\t\t\t\t\n\t\t\t\t, resulting,
where \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tF\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\t(4)\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t=\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tv\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\tdefines an auxiliary control input variable. The expression (10) can be rewritten of the following form:
For simplicity, we will denote the integral \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t0\n\t\t\t\t\t\t\t\t\tt\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tϕ\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t(\n\t\t\t\t\t\t\t\t\tτ\n\t\t\t\t\t\t\t\t\t)\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\td\n\t\t\t\t\t\t\t\tτ\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\tby \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tϕ\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t and \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t0\n\t\t\t\t\t\t\t\t\tt\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t0\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\tσ\n\t\t\t\t\t\t\t\t\t\t\t1\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t⋯\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t0\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\tσ\n\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\t\tn\n\t\t\t\t\t\t\t\t\t\t\t\t−\n\t\t\t\t\t\t\t\t\t\t\t\t1\n\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tϕ\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t(\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\tσ\n\t\t\t\t\t\t\t\t\t\t\tn\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t)\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\td\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tσ\n\t\t\t\t\t\t\t\t\tn\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t⋯\n\t\t\t\t\t\t\t\td\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tσ\n\t\t\t\t\t\t\t\t\t1\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t by \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\t(\n\t\t\t\t\t\t\t\t\t\t\tn\n\t\t\t\t\t\t\t\t\t\t\t)\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tϕ\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t with \n\t\t\t\t\t\t\n\t\t\t\t\t\t\tn\n\t\t\t\t\t\t\n\t\t\t\t\ta positive integer.
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The relations between the state variables and the integrally reconstructed states are given by
where\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tF\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\t(3)\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t(0)\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t, \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tF\n\t\t\t\t\t\t\t\t\t¨\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t(0)\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\tand \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tF\n\t\t\t\t\t\t\t\t\t˙\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t(0)\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t are all real constants depending on the unknown initial conditions.
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3.2. Sliding mode and GPI control
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GPI control is based on the use of integral reconstructors of the unmeasured state variables and the output error is integrally compensated. The sliding surface inspired on the GPI control technique can be proposed as
The last integral term yields error compensation, eliminating destabilizing effects, those of the structural estimation errors. The ideal sliding condition \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tσ\n\t\t\t\t\t\t\t\t\t^\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t=0\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t results in a sixth order dynamics,
The gains of the controller \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tα\n\t\t\t\t\t\t\t\t\t5\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t,\n\t\t\t\t\t\t\t\t…\n\t\t\t\t\t\t\t\t,\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tα\n\t\t\t\t\t\t\t\t\t0\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t are selected so that the associated characteristic polynomial \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\ts\n\t\t\t\t\t\t\t\t\t6\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t+\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tα\n\t\t\t\t\t\t\t\t\t5\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\ts\n\t\t\t\t\t\t\t\t\t5\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t+\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tα\n\t\t\t\t\t\t\t\t\t4\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\ts\n\t\t\t\t\t\t\t\t\t4\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t+\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tα\n\t\t\t\t\t\t\t\t\t3\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\ts\n\t\t\t\t\t\t\t\t\t3\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t+\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tα\n\t\t\t\t\t\t\t\t\t2\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\ts\n\t\t\t\t\t\t\t\t\t2\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t+\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tα\n\t\t\t\t\t\t\t\t\t1\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\ts\n\t\t\t\t\t\t\t\t+\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tα\n\t\t\t\t\t\t\t\t\t0\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t is Hurwitz. As a consequence, the error dynamics on the switching surface \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tσ\n\t\t\t\t\t\t\t\t\t^\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t=0\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t is globally asymptotically stable.
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The sliding surface \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tσ\n\t\t\t\t\t\t\t\t\t^\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t=0\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t is made globally attractive with the continuous approximation to the discontinuous sliding mode controller as given in (Sira-Ramírez, 1993), i.e., by forcing to satisfy the dynamics,
where \n\t\t\t\t\t\t\n\t\t\t\t\t\t\tμ\n\t\t\t\t\t\t\n\t\t\t\t\t and \n\t\t\t\t\t\t\n\t\t\t\t\t\t\tγ\n\t\t\t\t\t\t\n\t\t\t\t\t denote real positive constants and “sign” is the standard signum function. The sliding surface is globally attractive, \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tσ\n\t\t\t\t\t\t\t\t\t^\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\tσ\n\t\t\t\t\t\t\t\t\t\t\t^\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t·\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t0\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\tfor\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tσ\n\t\t\t\t\t\t\t\t\t^\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t≠\n\t\t\t\t\t\t\t\t0\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t, which is a very well known condition for the existence of sliding mode presented in (Utkin, 1978). Then the following sliding-mode controller is obtained
This controller requires only the measurement of the variables of state \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tz\n\t\t\t\t\t\t\t\t\ts\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t and \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tz\n\t\t\t\t\t\t\t\t\tu\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t corresponding to the vertical displacements of the body of the car and the wheel, respectively.
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4. Control of hydraulic suspension system
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The mathematical model of active suspension system shown in Fig. 1(c) is given by the equations (5) and (6). Using the same state variables definition than the control of electromagnetic suspension system, the representation in the state space form is as follows:
The net force provided by the hydraulic actuator as control input\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tu\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t=\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tF\n\t\t\t\t\t\t\t\tA\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t−\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tF\n\t\t\t\t\t\t\t\tf\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t, is the difference between the hydraulic force \n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tF\n\t\t\t\t\t\t\t\tA\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t and the frictional force\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tF\n\t\t\t\t\t\t\t\tf\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t.
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The system is controllable and flat (Fliess et al., 1993; Sira-Ramírez & Agrawal, 2004), with positions of the body of the car and wheel as output\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tF\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t=\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tm\n\t\t\t\t\t\t\t\ts\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tx\n\t\t\t\t\t\t\t\t1\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t+\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tm\n\t\t\t\t\t\t\t\tu\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tx\n\t\t\t\t\t\t\t\t3\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t, (Chávez et al., 2009). The controllability matrix and coefficients are:
It is assumed that \n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tk\n\t\t\t\t\t\t\t\tt\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tz\n\t\t\t\t\t\t\t\tr\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t=0\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t in the analysis of the differential flatness for the suspension system. To show the parameterization of the state variables and control input, we first formulate the time derivatives for\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tF\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t=\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tm\n\t\t\t\t\t\t\t\ts\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tx\n\t\t\t\t\t\t\t\t1\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t+\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tm\n\t\t\t\t\t\t\t\tu\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tx\n\t\t\t\t\t\t\t\t3\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t up to fourth order, resulting,
where\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tF\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\t(4)\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t=\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tv\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t, defines the auxiliary control input. Expression (19) can be rewritten in the following form:
For simplicity, we have denoted the integral \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t0\n\t\t\t\t\t\t\t\t\tt\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tϕ\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t(\n\t\t\t\t\t\t\t\t\tτ\n\t\t\t\t\t\t\t\t\t)\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\td\n\t\t\t\t\t\t\t\tτ\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\tby \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tϕ\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t and \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t0\n\t\t\t\t\t\t\t\t\tt\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t0\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\tσ\n\t\t\t\t\t\t\t\t\t\t\t1\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t⋯\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t0\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\tσ\n\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\t\tn\n\t\t\t\t\t\t\t\t\t\t\t\t−\n\t\t\t\t\t\t\t\t\t\t\t\t1\n\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tϕ\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t(\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\tσ\n\t\t\t\t\t\t\t\t\t\t\tn\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t)\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\td\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tσ\n\t\t\t\t\t\t\t\t\tn\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t⋯\n\t\t\t\t\t\t\t\td\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tσ\n\t\t\t\t\t\t\t\t\t1\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t by \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\t(\n\t\t\t\t\t\t\t\t\t\t\tn\n\t\t\t\t\t\t\t\t\t\t\t)\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tϕ\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t with \n\t\t\t\t\t\t\n\t\t\t\t\t\t\tn\n\t\t\t\t\t\t\n\t\t\t\t\tas a positive integer.
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The relationship between the state variables and the integrally reconstructed state variables is given by
where\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tF\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\t(3)\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t(0)\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t, \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tF\n\t\t\t\t\t\t\t\t\t¨\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t(0)\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\tand \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tF\n\t\t\t\t\t\t\t\t\t˙\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t(0)\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t are all real constants depending on the unknown initial conditions.
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4.2. Sliding mode and GPI control
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The sliding surface inspired on the GPI control technique is proposed according to equations (12), (13), and (14). This sliding surface is globally attractive (Utkin, 1978). Then the following sliding-mode controller is obtained:
This controller requires only the measurement of the variables of state \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tz\n\t\t\t\t\t\t\t\t\ts\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t and \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tz\n\t\t\t\t\t\t\t\t\tu\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t corresponding to the vertical positions of the body of the car and the wheel, respectively.
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5. Instrumentation of active suspension system
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5.1. Measurements required
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The only variables required for implementation of the proposed controllers are the vertical displacement of the body of the car\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tz\n\t\t\t\t\t\t\t\t\ts\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t, and the vertical displacement of the wheel\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tz\n\t\t\t\t\t\t\t\t\tu\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t. These variables are needed to be measured by sensors.
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5.2. Using sensors
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In (Chamseddine et al., 2006), the use of sensors in experimental vehicle platforms, as well as in commercial vehicles is presented. The most common sensors, used for measuring the vertical displacement of the body of the car and the wheels, are laser sensors. This type of sensor could be used to measure the variables \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tz\n\t\t\t\t\t\t\t\t\ts\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t and \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tz\n\t\t\t\t\t\t\t\t\ts\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t needed for implementation of the controllers. Accelerometers or other types of sensors are not needed for measuring the variables \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\tz\n\t\t\t\t\t\t\t\t\t\t˙\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\ts\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t and\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\tz\n\t\t\t\t\t\t\t\t\t\t˙\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tu\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t; these variables are estimated with the use of integral reconstruction from knowledge of the control input, the flat output and the differentially flat system model.
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The schematic diagram of the instrumentation of the active suspension system is illustrated in Fig. 2.
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Figure 2.
Schematic diagram of the instrumentation of the active suspension system.
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6. Simulation results with MATLAB/Simulink
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The simulation results were obtained by means of MATLAB/Simulink\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t®\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t, with the Runge-Kutta numerical method and a fixed integration step of\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t1\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\tm\n\t\t\t\t\t\t\ts\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t.
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6.1. Parameters and type of road disturbance
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The numerical values of the quarter-car suspension model parameters (Sam & Hudha, 2006) chosen for the simulations are shown in Table 1.
Spring stifness, \n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\tk\n\t\t\t\t\t\t\t\t\t\t\ts\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t
with \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\ta\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t=0.11\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t[m] for\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t0.5\n\t\t\t\t\t\t\t\t≤\n\t\t\t\t\t\t\t\tt\n\t\t\t\t\t\t\t\t≤\n\t\t\t\t\t\t\t\t0.75\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t, \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\ta\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t=0.55\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t[m] for \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t3.0\n\t\t\t\t\t\t\t\t≤\n\t\t\t\t\t\t\t\tt\n\t\t\t\t\t\t\t\t≤\n\t\t\t\t\t\t\t\t3.25\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\tand 0 otherwise.
\n\t\t\t\t
Figure 3.
Type of road disturbance.
\n\t\t\t\t
The road disturbance was programmed into Simulink blocks, as shown in Fig. 4. Here, the block called “conditions” was developed as a Simulink subsystem block Fig. 5.
\n\t\t\t\t
Figure 4.
Type of road disturbance in Simulink.
\n\t\t\t\t
Figure 5.
Conditions of road disturbance in Simulink.
\n\t\t\t
\n\t\t\t
\n\t\t\t\t
6.2. Passive vehicle suspension system
\n\t\t\t\t
Some simulation results of the passive suspension system performance are shown in Fig. 6. The Simulink model of the passive suspension system used for the simulations is shown in Fig. 7.
\n\t\t\t\t
Figure 6.
Simulation results of passive suspension system, where the suspension deflection is given by (zs − zu) and the tire deflection by (zu − zr).
\n\t\t\t
\n\t\t\t
\n\t\t\t\t
6.3. Control of electromagnetic suspension system
\n\t\t\t\t
It is desired to stabilize the system at the positions \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tz\n\t\t\t\t\t\t\t\t\ts\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t=0\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t and\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tz\n\t\t\t\t\t\t\t\t\tu\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t=0\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t. The controller gains were obtained by forcing the closed loop characteristic polynomial to be given by the following Hurwitz polynomial:
The Simulink model of the sliding mode based GPI controller of the active suspension system is shown in Fig. 8. The simulation results are illustrated in Fig. 9 It can be seen the high vibration attenuation level of the active vehicle suspension system compared with the passive counterpart.
\n\t\t\t\t
Figure 7.
Simulink model of the passive suspension system.
\n\t\t\t\t
Figure 8.
Simulink model of the sliding mode based GPI controller.
\n\t\t\t\t
Figure 9.
Simulation results of the sliding mode based GPI controller of the electromagnetic suspension system.
\n\t\t\t\t
Figure 10.
Simulation results of sliding mode based GPI controller of hydraulic suspension system.
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\n\t\t\t
\n\t\t\t\t
6.3. Control of hydraulic suspension system
\n\t\t\t\t
It is desired to stabilize the system in the positions \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tz\n\t\t\t\t\t\t\t\t\ts\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t=0\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t and\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tz\n\t\t\t\t\t\t\t\t\tu\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t=0\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t. The controller gains were obtained by forcing the closed loop characteristic polynomial to be given by the following Hurwitz polynomial:
with\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tp\n\t\t\t\t\t\t\t\t\t3\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t=90\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t, \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tp\n\t\t\t\t\t\t\t\t\t4\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t=90\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t, \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tζ\n\t\t\t\t\t\t\t\t\t2\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t=0.9\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t, \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tω\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\tn\n\t\t\t\t\t\t\t\t\t\t2\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t=70\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t, \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tμ\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t=95\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\tand\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tγ\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t=95\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t. The performance of the sliding mode based GPI controller is depicted in Fig. 10. One can see the high attenuation level of road-induced vibrations with respect to passive suspension system.
\n\t\t\t\t
The same Matlab/Simulink simulation programs were used to implement the controllers for the electromagnetic and hydraulic active suspension systems. For the electromagnetic active suspension system, it is assumed that c\n\t\t\t\t\t\n\t\t\t\t\t\tz\n\t\t\t\t\t\n\t\t\t\t\t= 0.
\n\t\t\t
\n\t\t
\n\t\t
\n\t\t\t
7. Conclusions
\n\t\t\t
In this chapter we have presented an approach of robust active vibration control schemes for electromagnetic and hydraulic vehicle suspension systems based on Generalized Proportional-Integral control, differential flatness and sliding modes. Two controllers have been proposed to attenuate the vibrations induced by unknown exogenous disturbance excitations due to irregular road surfaces. The main advantage of the controllers proposed, is that they require only measurements of the position of the car body and the tire. Integral reconstruction is employed to get structural estimates of the time derivatives of the flat output, needed for the implementation of the controllers proposed. The simulation results show that the stabilization of the vertical position of the quarter of car is obtained within a period of time much shorter than that of the passive suspension system. The fast stabilization with amplitude in acceleration and speed of the body of the car is observed. Finally, the robustness of the controllers to stabilize to the system before the unknown disturbance is verified.
\n\t\t
\n\t\n',keywords:null,chapterPDFUrl:"https://cdn.intechopen.com/pdfs/18570.pdf",chapterXML:"https://mts.intechopen.com/source/xml/18570.xml",downloadPdfUrl:"/chapter/pdf-download/18570",previewPdfUrl:"/chapter/pdf-preview/18570",totalDownloads:7251,totalViews:845,totalCrossrefCites:1,totalDimensionsCites:3,hasAltmetrics:0,dateSubmitted:"November 29th 2010",dateReviewed:"April 30th 2011",datePrePublished:null,datePublished:"September 9th 2011",dateFinished:null,readingETA:"0",abstract:null,reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/18570",risUrl:"/chapter/ris/18570",book:{slug:"applications-of-matlab-in-science-and-engineering"},signatures:"Esteban Chávez Conde, Francisco Beltrán Carbajal Antonio Valderrábano González and Ramón Chávez Bracamontes",authors:[{id:"10444",title:"Dr.",name:"Francisco",middleName:null,surname:"Beltran-Carbajal",fullName:"Francisco Beltran-Carbajal",slug:"francisco-beltran-carbajal",email:"fran_belt29@hotmail.com",position:null,institution:{name:"Universidad Autónoma Metropolitana",institutionURL:null,country:{name:"Mexico"}}},{id:"38737",title:"Dr.",name:"Antonio",middleName:null,surname:"Valderrabano-Gonzalez",fullName:"Antonio Valderrabano-Gonzalez",slug:"antonio-valderrabano-gonzalez",email:"antonio.valderrabano@upjal.edu.mx",position:null,institution:{name:"Universidad Panamericana",institutionURL:null,country:{name:"Guatemala"}}},{id:"53625",title:"M.Sc.",name:"Esteban",middleName:null,surname:"Chavez-Conde",fullName:"Esteban Chavez-Conde",slug:"esteban-chavez-conde",email:"chavez.conde@gmail.com",position:null,institution:{name:"Universidad del Papaloapan",institutionURL:null,country:{name:"Mexico"}}},{id:"94367",title:"MSc.",name:"Ramon",middleName:null,surname:"Chavez Bracamontes",fullName:"Ramon Chavez Bracamontes",slug:"ramon-chavez-bracamontes",email:"ramonitcg@hotmail.com",position:"Professor",institution:null}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Quarter-car suspension systems",level:"1"},{id:"sec_2_2",title:"2.1. Mathematical model of passive suspension system",level:"2"},{id:"sec_3_2",title:"2.2. Mathematical model of active electromagnetic suspension system",level:"2"},{id:"sec_4_2",title:"2.3. Mathematical model of hydraulic active suspension system",level:"2"},{id:"sec_6",title:"3. Control of electromagnetic suspension system",level:"1"},{id:"sec_6_2",title:"3.1. Integral reconstructors",level:"2"},{id:"sec_7_2",title:"3.2. Sliding mode and GPI control",level:"2"},{id:"sec_9",title:"4. Control of hydraulic suspension system",level:"1"},{id:"sec_9_2",title:"4.1. Integral reconstructors",level:"2"},{id:"sec_10_2",title:"4.2. Sliding mode and GPI control",level:"2"},{id:"sec_12",title:"5. Instrumentation of active suspension system",level:"1"},{id:"sec_12_2",title:"5.1. Measurements required",level:"2"},{id:"sec_13_2",title:"5.2. Using sensors",level:"2"},{id:"sec_15",title:"6. Simulation results with MATLAB/Simulink",level:"1"},{id:"sec_15_2",title:"6.1. Parameters and type of road disturbance",level:"2"},{id:"sec_16_2",title:"6.2. Passive vehicle suspension system",level:"2"},{id:"sec_17_2",title:"6.3. Control of electromagnetic suspension system",level:"2"},{id:"sec_18_2",title:"6.3. Control of hydraulic suspension system",level:"2"},{id:"sec_20",title:"7. 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G.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tDa\n\t\t\t\t\t\t\tSilva. F. P.\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t2006Permanent-Magnets Linear Actuators Applicability in Automobile Active Suspensions”, IEEE Trans. on Vehicular Technology. 55\n\t\t\t\t\t1\n\t\t\t\t\t86\n\t\t\t\t\t94January.\n\t\t\t'},{id:"B10",body:'\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tSam\n\t\t\t\t\t\t\tY. M.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tHudha\n\t\t\t\t\t\t\tK.\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t2006Modelling and Force Tracking Control of Hydraulic Actuator for an Active Suspension System”, IEEE ICIEA,.\n\t\t\t'},{id:"B11",body:'\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tSira-Ramírez\n\t\t\t\t\t\t\tH.\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t1993A dynamical variable structure control strategy in asymptotic output tracking problems”, IEEE Trans. on Automatic Control. 38\n\t\t\t\t\t4\n\t\t\t\t\t615\n\t\t\t\t\t620April.\n\t\t\t'},{id:"B12",body:'\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tSira-Ramírez\n\t\t\t\t\t\t\tH.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tAgrawal\n\t\t\t\t\t\t\tSunil. K.\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t2004Differentially Flat Systems”, Marcel Dekker, N.Y.,.\n\t\t\t'},{id:"B13",body:'\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tTahboub\n\t\t\t\t\t\t\tKarim. A.\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t2005Active Nonlinear Vehicle-Suspension Variable-Gain Control”, 13th IEEE Mediterranean Conference on Control and Automation, 569\n\t\t\t\t\t574Limassol, Cyprus, June 27-29,.\n\t\t\t'},{id:"B14",body:'\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tTahboub\n\t\t\t\t\t\t\tKarim. A.\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t2005Active Nonlinear Vehicle-Suspension Variable-Gain Control”, 13th IEEE Mediterranean Conference on Control and Automation, 569\n\t\t\t\t\t574Limassol, Cyprus, June 27-29,.\n\t\t\t'},{id:"B15",body:'\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tUtkin\n\t\t\t\t\t\t\tV. I.\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t1978Sliding Modes and Their Applications in Variable Structure Systems”. Moscow: MIR,.\n\t\t\t'},{id:"B16",body:'\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tYousefi\n\t\t\t\t\t\t\tA.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tAkbari\n\t\t\t\t\t\t\tA.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tLohmann\n\t\t\t\t\t\t\tB.\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t2006Low Order Robust Controllers for Active Vehicle Suspensions”, IEEE International Conference on Control Applications, 693\n\t\t\t\t\t698Munich, Germany, October 4-6,.\n\t\t\t'}],footnotes:[],contributors:[{corresp:null,contributorFullName:"Esteban Chávez Conde",address:null,affiliation:'
Universidad del Papaloapan, Campus Loma Bonita, México
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Instrumentation",slug:"modelling-and-simulation-of-ph-neutralization-plant-including-the-process-instrumentation",totalDownloads:7587,totalCrossrefCites:1,signatures:"Claudio Garcia and Rodrigo Juliani Correa De Godoy",authors:[{id:"59058",title:"Dr.",name:"Claudio",middleName:null,surname:"Garcia",fullName:"Claudio Garcia",slug:"claudio-garcia"},{id:"59059",title:"D.Sc.",name:"Rodrigo",middleName:null,surname:"Juliani",fullName:"Rodrigo Juliani",slug:"rodrigo-juliani"}]}]},relatedBooks:[{type:"book",id:"2160",title:"MATLAB",subtitle:"A Fundamental Tool for Scientific Computing and Engineering Applications - Volume 1",isOpenForSubmission:!1,hash:"dd9c658341fbd264ed4f8d9e6aa8ca29",slug:"matlab-a-fundamental-tool-for-scientific-computing-and-engineering-applications-volume-1",bookSignature:"Vasilios N. Katsikis",coverURL:"https://cdn.intechopen.com/books/images_new/2160.jpg",editedByType:"Edited by",editors:[{id:"12289",title:"Prof.",name:"Vasilios",surname:"Katsikis",slug:"vasilios-katsikis",fullName:"Vasilios Katsikis"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"},chapters:[{id:"39372",title:"PID Control Design",slug:"pid-control-design",signatures:"A.B. 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Fagerstrom",slug:"sven-e.-fagerstrom"},{id:"149266",title:"Dr.",name:"Nagy",middleName:null,surname:"Bengiamin",fullName:"Nagy Bengiamin",slug:"nagy-bengiamin"}]},{id:"39333",title:"Improved DTC Algorithms for Reducing Torque and Flux Ripples of PMSM Based on Fuzzy Logic and PWM Techniques",slug:"improved-dtc-algorithms-for-reducing-torque-and-flux-ripples-of-pmsm-based-on-fuzzy-logic-and-pwm-te",signatures:"Khalid Chikh, Mohamed Khafallah and Abdallah Saâd",authors:[{id:"145063",title:"Ph.D.",name:"Khalid",middleName:null,surname:"Chikh",fullName:"Khalid Chikh",slug:"khalid-chikh"},{id:"146138",title:"Prof.",name:"Mohamed",middleName:null,surname:"Khafallah",fullName:"Mohamed Khafallah",slug:"mohamed-khafallah"},{id:"149147",title:"Prof.",name:"Abdallah",middleName:null,surname:"Saâd",fullName:"Abdallah Saâd",slug:"abdallah-saad"}]},{id:"39327",title:"Position Estimation of the PMSM High Dynamic Drive at Low Speed Range",slug:"position-estimation-of-the-pmsm-high-dynamic-drive-at-low-speed-range",signatures:"Konrad Urbanski",authors:[{id:"148958",title:"Dr.",name:"Konrad",middleName:null,surname:"Urbanski",fullName:"Konrad Urbanski",slug:"konrad-urbanski"}]},{id:"39377",title:"Digital Differential Protection of Power Transformer Using Matlab",slug:"digital-differential-protection-of-power-transformer-using-matlab",signatures:"Adel Aktaibi and M. Azizur Rahman",authors:[{id:"124154",title:"Prof.",name:"Azizur",middleName:null,surname:"Rahman",fullName:"Azizur Rahman",slug:"azizur-rahman"},{id:"146799",title:"Dr.",name:"Adel",middleName:null,surname:"Aktaibi",fullName:"Adel Aktaibi",slug:"adel-aktaibi"}]},{id:"39371",title:"PH Control Using MATLAB",slug:"ph-control-using-matlab",signatures:"Mostefa Ghassoul",authors:[{id:"146702",title:"Dr.",name:"Mostefa",middleName:null,surname:"Ghassoul",fullName:"Mostefa Ghassoul",slug:"mostefa-ghassoul"}]},{id:"39330",title:"An Advanced Transmission Line and Cable Model in Matlab for the Simulation of Power-System Transients",slug:"an-advanced-transmission-line-and-cable-model-in-matlab-for-the-simulation-of-power-system-transient",signatures:"Octavio Ramos-Leaños, Jose Luis Naredo and Jose Alberto Gutierrez-Robles",authors:[{id:"145421",title:"Dr.",name:"Octavio",middleName:null,surname:"Ramos-Leaños",fullName:"Octavio Ramos-Leaños",slug:"octavio-ramos-leanos"},{id:"145517",title:"Dr.",name:"Jose Luis",middleName:null,surname:"Naredo",fullName:"Jose Luis Naredo",slug:"jose-luis-naredo"},{id:"145519",title:"Dr.",name:"Jose Alberto",middleName:null,surname:"Gutierrez-Robles",fullName:"Jose Alberto Gutierrez-Robles",slug:"jose-alberto-gutierrez-robles"}]},{id:"39328",title:"A New Modeling of the Non-Linear Inductances in MATLAB",slug:"a-new-modeling-of-the-non-linear-inductances-in-matlab",signatures:"M. Ould Ahmedou, M. Ferfra, M. Chraygane and M. Maaroufi",authors:[{id:"145391",title:"PhD.",name:"Mohamed Ould",middleName:null,surname:"Ahmedou",fullName:"Mohamed Ould Ahmedou",slug:"mohamed-ould-ahmedou"},{id:"148288",title:"Prof.",name:"Mohammed",middleName:null,surname:"Ferfra",fullName:"Mohammed Ferfra",slug:"mohammed-ferfra"},{id:"148289",title:"Prof.",name:"Mohammed",middleName:null,surname:"Chraygane",fullName:"Mohammed Chraygane",slug:"mohammed-chraygane"},{id:"148628",title:"Prof.",name:"Mohammed",middleName:null,surname:"Maaroufi",fullName:"Mohammed Maaroufi",slug:"mohammed-maaroufi"}]},{id:"39378",title:"Dynamic Simulation of Electrical Machines and Drive Systems Using MATLAB GUI",slug:"dynamic-simulation-of-electrical-machines-and-drive-systems-using-matlab-gui",signatures:"Viliam Fedák, Tibor Balogh and Pavel Záskalický",authors:[{id:"85462",title:"Associate Prof.",name:"Viliam",middleName:null,surname:"Fedak",fullName:"Viliam Fedak",slug:"viliam-fedak"},{id:"145228",title:"MSc.",name:"Tibor",middleName:null,surname:"Balogh",fullName:"Tibor Balogh",slug:"tibor-balogh"},{id:"154498",title:"Prof.",name:"Pavel",middleName:null,surname:"Záskalický",fullName:"Pavel Záskalický",slug:"pavel-zaskalicky"}]},{id:"39363",title:"Image Reconstruction Methods for MATLAB Users - A Moore-Penrose Inverse Approach",slug:"image-reconstruction-methods-for-matlab-users-a-moore-penrose-inverse-approach",signatures:"S. Chountasis, V.N. Katsikis and D. Pappas",authors:[{id:"12289",title:"Prof.",name:"Vasilios",middleName:"N.",surname:"Katsikis",fullName:"Vasilios Katsikis",slug:"vasilios-katsikis"},{id:"150079",title:"Dr.",name:"Dimitrios",middleName:null,surname:"Pappas",fullName:"Dimitrios Pappas",slug:"dimitrios-pappas"},{id:"150080",title:"Dr.",name:"Spiros",middleName:null,surname:"Chountasis",fullName:"Spiros Chountasis",slug:"spiros-chountasis"}]},{id:"39325",title:"Artificial Human Arm Driven by EMG Signal",slug:"artificial-human-arm-driven-by-emg-signal",signatures:"Mohammed Z. Al-Faiz and Abbas H. Miry",authors:[{id:"145422",title:"Prof.",name:"Mohammed Zeki",middleName:null,surname:"Al-Faiz",fullName:"Mohammed Zeki Al-Faiz",slug:"mohammed-zeki-al-faiz"}]},{id:"39369",title:"Analysis and Modeling of Clock-Jitter Effects in Delta-Sigma Modulators",slug:"analysis-and-modeling-of-clock-jitter-effects-in-delta-sigma-modulators",signatures:"Ramy Saad, Sebastian Hoyos and Samuel Palermo",authors:[{id:"144896",title:"Dr.",name:"Ramy",middleName:null,surname:"Saad",fullName:"Ramy Saad",slug:"ramy-saad"},{id:"154354",title:"Prof.",name:"Sebastian",middleName:null,surname:"Hoyos",fullName:"Sebastian Hoyos",slug:"sebastian-hoyos"},{id:"154355",title:"Prof.",name:"Samuel",middleName:null,surname:"Palermo",fullName:"Samuel Palermo",slug:"samuel-palermo"}]},{id:"39379",title:"Matlab-Based Algorithm for Real Time Analysis of Multiexponential Transient Signals",slug:"matlab-based-algorithm-for-real-time-analysis-of-multiexponential-transient-signals",signatures:"Momoh-Jimoh E. Salami, Ismaila B. Tijani, Abdussamad U. Jibia and Za'im Bin Ismail",authors:[{id:"90923",title:"Prof.",name:"Momoh-Jimoh",middleName:"Eyiomika",surname:"Salami",fullName:"Momoh-Jimoh Salami",slug:"momoh-jimoh-salami"}]},{id:"39362",title:"Digital FIR Hilbert Transformers: Fundamentals and Efficient Design Methods",slug:"digital-fir-hilbert-transformers-fundamentals-and-efficient-design-methods",signatures:"David Ernesto Troncoso Romero and Gordana Jovanovic Dolecek",authors:[{id:"148249",title:"Prof.",name:"Gordana",middleName:null,surname:"Jovanovic Dolecek",fullName:"Gordana Jovanovic Dolecek",slug:"gordana-jovanovic-dolecek"},{id:"148250",title:"Dr.",name:"David Ernesto",middleName:null,surname:"Troncoso Romero",fullName:"David Ernesto Troncoso Romero",slug:"david-ernesto-troncoso-romero"}]},{id:"39334",title:"Detection of Craters and Its Orientation on Lunar",slug:"detection-of-craters-and-its-orientation-on-lunar",signatures:"Nur Diyana Kamarudin, Kamaruddin Abd. Ghani, Siti Noormiza Makhtar, Baizura Bohari and Noorlina Zainuddin",authors:[{id:"145341",title:"Mrs.",name:"Nur Diyana",middleName:null,surname:"Kamarudin",fullName:"Nur Diyana Kamarudin",slug:"nur-diyana-kamarudin"},{id:"145654",title:"Mrs.",name:"Siti Noormiza",middleName:null,surname:"Makhtar",fullName:"Siti Noormiza Makhtar",slug:"siti-noormiza-makhtar"},{id:"145655",title:"Mrs.",name:"Noorlina",middleName:null,surname:"Zainuddin",fullName:"Noorlina Zainuddin",slug:"noorlina-zainuddin"},{id:"145657",title:"Mrs.",name:"Baizura",middleName:null,surname:"Bohari",fullName:"Baizura Bohari",slug:"baizura-bohari"},{id:"150893",title:"Prof.",name:"Kamaruddin",middleName:null,surname:"Abd. Ghani",fullName:"Kamaruddin Abd. Ghani",slug:"kamaruddin-abd.-ghani"}]}]}]},onlineFirst:{chapter:{type:"chapter",id:"75754",title:"A Comprehensive Review on Available/Existing Renewable Energy Systems in Malaysia and Comparison of Their Capability of Electricity Generation in Malaysia",doi:"10.5772/intechopen.96586",slug:"a-comprehensive-review-on-available-existing-renewable-energy-systems-in-malaysia-and-comparison-of-",body:'\n
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1. Introduction to renewable energies
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The demand for electricity increases new ways of electrical generation are required that is both cleaner and safer. In Malaysia, research has shown that about 3.8% of the population reside below the poverty line. Most of these people are located in rural areas in Malaysia. The electricity coverage in Peninsular Malaysia is at 99.62%, while Sabah and Sarawak’s electrical coverage is around 79%. The challenge is to build a grid system through jungles and mountain. To add to that, building a grid system through these types of the area will also not be economic. A way to solve the problem would be through the implementation of Renewable Energy (RE) in these villages. The main source of Malaysia’s energy supplies is from Natural Gas, Hydro, Oil, RE and Coal. Among these five Energy Sources (ES), coal supplies the most energy in terms of electricity production at 26,177 GWh. The types of RE which were researched are Solar, Wind and Hydropower. Not all of these energies are widely used in Malaysia. Some Renewable Energy Sources (RES) are ideal because of the terrain or weather in Malaysia, while others are under the research phase to determine the possibility of implementation in Malaysia. Malaysia has been amply endowed RESs such as Solar and Biomass Energy. However, these ESs have been greatly underutilized. A comparison of each REs was done to understanding the applicability of each of these resources in the Malaysian context. Being able to implement these ESs especially in areas not connected to the national grid would be beneficial to Malaysia to improve the living quality of Malaysians in rural areas.
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2. Malaysia solar energy information
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2.1 Introduction to solar energy
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Sun is the ultimate resource on earth as it is responsible for all the weather conditions and ESs on earth. Sun emits Solar Energy due to the nuclear fusion reactions in the sun’s core and subsequently produces a tremendous amount of energy. However, small portion of it is directed towards earth in the form of light and heat. Solar energy, which correlates to the sunlight’s photons has an abundant potential that can fill our global needs if it is harnessed in the right way.
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Generally, there are two main ways to harness Solar Energy, which is using either photovoltaics or solar thermal collectors. Photovoltaic (PV) or commonly known as solar cells, comes in various shapes and are made from electricity producing materials such monocrystalline silicon, polycrystalline silicon and thin film solar cells. When sunlight gets in contact with the solar cells’ semiconductor material, they get absorbed and consequently, generate electricity [1]. This conversion is mainly due to the photovoltaic effect. When this effect occurs, the photons from the sun’s radiation knocks electrons loose, causing them to flow and thus generate electricity. The initial generated current is the direct current (DC). In order for, this can be stored in the battery and used for DC appliances. To make it useable for regular households, it is first converted to alternating current (AC) using an inverter. If the system is connected to the grid, then additional electricity is fed to the main supply. The other way of tapping the sun’s energy is by capturing the heat produced by the solar radiation. This form of harnessing is usually done in a large scale in such a fashion that power stations are built. These power stations are called Concentrated Solar Power (CSP) plants. The term concentrated comes from a large number of mirrors in the plant which are used to focus the sun’s rays on tubes containing molten fluid that can store heat well. The molten fluid then is used to convert water into steam. Subsequently, the steam produced rotates a turbine and thus, generate electricity [2].
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In Malaysia, solar cells are commonly used to generate electricity. In 2018 alone, 467344.2 MWh of power was generated based on Malaysia’s Feed-in Tariff (FiT) system. Comparing this figure to the other RE, harnessing solar energy comes up on top. Although the nation is exposed to long hours of sunlight daily, the average maximum amount of energy produced per solar cell has an efficiency of 15–20 percent. This efficiency poses an issue whereby not many investors would invest in the technology. A way to overcome this situation in Malaysia is by constructing Large Scale Solar (LSS) power plants. This way, the amount of electricity generated can be maximized. The LSS power plants are not to be mistaken with CSP plants. The main difference between the two is that LSS captures light via solar cells and converting them into electricity whereas CSP captures heat which is transformed into mechanical energy that rotates a turbine and subsequently produces electricity. In Malaysia, CSPs are not developed yet. Having the minimal Direct Normal Irradiance (DNI) within the range of 1900 to 2000 kWh/m2/year, is the main requirement to start a CSP project. However, the DNI for Malaysia is below this threshold and it is due to the geographical position of the country which is not situated in high solar insolation zones [2].
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2.2 Solar energy in Malaysia
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2.2.1 Pajam, Negeri Sembilan
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On 20th March 2012, an 8 MW large scale solar PV plant, developed by Cypark Resources Berhad, was officially launched and operational. Figure 1 shows the aerial view of the solar power plant. This project is the first-ever completed LSS above 1 MW and operational under the Sustainable Energy Development Authority’s (SEDA) Feed-In-Tariff Mechanism (FiT) in Malaysia. The LSS has received two accolades by the Malaysia Book of Records as it is recognized as one of the largest grids connected solar parks in the nation. The land coverage by the LSS is approximately 41.73 acres and it is equipped with 31, 824 solar panels [3]. Being the first of its kind in the country, the RM150 million project has the ability to power over 17,000 households annually. In 21 years from its initiation, it is expected to generate up to RM500 million worth of electricity. This is equivalent to the power generated by 9, 300 tons of coal each year. For the environment, it is capable of reducing 14, 335 tons of carbon emissions and 664 tons of methane gas annually [3, 4].
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Figure 1.
Aerial view of three major Solar Energy Projects in Malaysia. (a) An aerial view of the 8 MW large scale solar photovoltaic plant [8], (b) An aerial view of Mukim Tanjung 12 Solar Photovoltaic Plant [9] and (c) An aerial view of Sungai Siput solar photovoltaic power plant [13].
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2.2.2 Mukim Tanjung 12, Kuala Selangat, Selangor
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As of November 2018, the nation’s largest LSS has started its operation. The project won in competitive bidding by Tenaga Nasional Berhard (TNB) and subsequently, the project started its development in July 2017. The 10 km of 132 kV power and fiber optic underground cables were connected to 230, 000 solar panels in this plant. This LSS is capable of producing 50 MW of electricity to the national grid. The total cost of this project is approximately RM339 million. The total land size used is up to 242.16 acres. Due to the success of TNB, this project serves as a booster and aspiration in further developing more RE projects in Malaysia. Consequently, by 2030, Energy, Science, Technology, Environment and Climate Change Ministry has set a goal to increase the country’s electricity usage powered by 20% based on Res [5] Also, TNB’s success in this project has led the company to secure RM144 million in developing a second large scale solar project for the country [5, 6] Figure 1 shows the aerial view of the LSS.
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2.2.3 Sungai Siput, Perak
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On 27 November 2018, one of Malaysia’s advance solar PV power plant has started its operation. This project began on 16 March 2017 when Sinar Kamiri Sdn Bhd signed a power purchase agreement with Tenaga Nasional Berhad to develop and operate a 49 MW large scale solar photovoltaic power plant which cost around RM270 million [6]. This LSS is situated in Sungai Siput Perak over a land size of 150 acres and is equipped with 170, 961 panels. In this land, the complex mountain topography has posed many challenges for the developers as this would often cause shadows, string mismatches as well as high temperature and humidity. However, the land offers a long duration of sunshine and high solar irradiance throughout the year. To overcome this topographical situation, the developers have integrated Huawei Fusion Solar Smart PV Solution into the grid [7]. This includes the smart PV string inverter SUN2000-42KTL to troubleshoot the string mismatch issues faced in Sungai Siput as well as a PLC technology which helps to deliver a simpler system with safer and more reliable data transmission. As a consequence of using these PV systems, this LSS has obtained 2% higher energy yields and a 50% increase in efficiency compared to other LSS of the same scale. Figure 1 illustrates the aerial view of the LSS.
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2.2.4 Kudat, Sabah
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In July 2017, RM250 million green socially responsible investment (SRI) sukuk has been issued to Tadau Energy Berhad to further develop the current state of RE usage in Malaysia. Also, this green SRI sukuk receives funds for the projects due to its international endorsement and potential tax benefits via deduction of issuing expenses against the taxable income of the issuer [8]. In other words, it helps companies to achieve their corporate social responsibilities. With this cash in hand, the company started to develop a 50 MW solar power plant in Kudat, Sabah which covers up to 189 acres. This LSS is equipped with 188, 512 solar panels. 2 MW out of 50 MW of the available power channels the local Kudat electricity grid while the remaining 48 MW is channeled into 132 kV transmission line which is distributed through Sabah [9].
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2.3 Comparing the projects
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Based on the information in Table 1, the selected 4 LSS projects can be arranged and compared between one another in terms of generation capacity, number of solar panels, generation capacity per solar panel, land area and project cost.
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Location
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Pajam, Negeri Sembilan
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Mukim Tanjung 12, Selangor
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Sungai Siput, Perak
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Kudat, Sabah
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Generation Capacity (MW)
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8
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50
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49
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50
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Number of Solar Panels
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31, 824
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230, 000
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170, 961
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188, 512
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Yield per Solar Panel (W/panel)
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251.38
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217.39
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286.61
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265.23
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Land Area (acres)
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41.73
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242.16
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150
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189
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Project Cost (RM in millions)
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150
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339
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270
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250
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Table 1.
Summary of information of the four selected LSS.
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First, among the projects, the LSS which has the highest generation capacities are Mukim Tanjung 12, Sungai Siput and Kudat. Each of these LSS has a generation capacity of around 50 MW. Subsequently, this is followed by Pajam at 8 MW. The difference in the capacities is based on the purpose of the project. For example, the reason why Kudat’s generation capacity is high is that the power generated is used to supply the local villages as the remaining is supplied to the power grid, which is then distributed throughout Sabah [9]. A smaller LSS may not have the same purpose and the demand for electricity in the area may not be as high as areas with more population or activities. Alongside this reasoning, it corresponds as well with the total number of panels. Although Mukim Tanjung 12, Sungai Siput and Kudat have similar generation capacity and project motives, the number of panels used at each plant is different. As seen in the table, Mukim Tanjung 12 uses 230, 000 panels, Sungai Siput uses 170, 961 panels and Kudat uses 188, 512 panels. Coinciding with this information, it can be inferred that the panels which are used in each power plant have different efficiencies. For instance, although Sungai Siput uses fewer solar panels compared to Mukim Tanjung 12 nad Kudat, it is still having a similar power output as the other two. This is because the panels which the LSS has, uses Huawei’s Fusion Solar Smart PV Solution panels. These panels have the potential to increase energy yields, maximize the return of investments (ROI) and helps customers optimize initial investments. Also, DC combiners are not needed in these plants [7, 8]. The reasoning in the paragraph is also backed up by the amount of each that each panel can generate. From the table based on the third row, the highest yielding panel to lowest is Sungai Siput at 286.61 W/panel, Kudat at 265.23 W/panel, Pajam at 251.31 W/panel then Mukim Tanjung 12 at 217.39 W/panel. From here, the quality of the panels used in both Sungai Siput and Kudat are of higher efficiency. Next, the amount of land size used from highest to lowest is in an order of Mukim Tanjung 12 at242.16 acres, Kudat at189 acres, Sungai Siput at 150 acres and lastly Pajam at 41.73 acres. The land coverage is closely dependent on the required generation capacity as well as the yield per panel. If the required generation capacity is low, the land size will not cover over a large area as seen in Pajam. Also, if the yield per panel is high, the land size needed is small. The last aspect that can be compared is the project cost. This correlates with the land size, efficiency of the panels and ease of installation. Generally, it would cost more for a land of a bigger size. This goes the same for a higher quality panel. In terms of ease of installation, it depends on the safety factors that are given to each component in the power plant based on the land’s topography and weather. Some areas could be flat land while some are covered by hills. In Mukim Tanjung 12, since its land size is large, it accounts for the high cost of the project. Subsequently, Sungai Siput’s project cost is relatively high as well and this is due to the hilly area which the LSS is built on as well as the quality of the solar panels.
\n
\n
\n
2.4 Comparing solar energy in Malaysia to the World
\n
In Malaysia, the country’s first LSS was developed in 2012. However, it does a gradual impact on the awareness of people on using RESs. Ever since then, more and more LSS projects have been developed and the country has started to see this RE’s advantages. Consequently, in the current years, the country has new policies such as the Renewable Energy Transition Roadmap (RETR) 2035 which aims to further explore the possible strategies and action plans to reach the country’s renewable target of 20% in the national power mic by 2025. In Table 2, the new addition in the panels is around the same value for each year. This is due to the country’s reliance on coal and fuel which has also been one of the main sources of the country’s economy. As a result, transitioning to another form of ES requires confidence built up by the country. Nonetheless, this issue is slowly alleviated as the awareness of using more RESs has increased every year.
\n
\n
\n
\n
\n
\n
\n
\n
\n
\n
\n\n
\n
\n
2015
\n
2016
\n
2017
\n
2018
\n
\n
\n
Country
\n
Total solar PV Addition (MW)
\n
Net Solar PV Capacity (MW)
\n
Total solar PV Addition (MW)
\n
Net Solar PV Capacity (MW)
\n
Total solar PV Addition (MW)
\n
Net Solar PV Capacity (MW)
\n
Total solar PV Addition (MW)
\n
Net Solar PV Capacity (MW)
\n
\n\n\n
\n
China
\n
15,150
\n
43,530
\n
34,540
\n
78,070
\n
53,000
\n
131,000
\n
44,018
\n
175,018
\n
\n
\n
US
\n
7,300
\n
25,620
\n
14,730
\n
33,100
\n
8,173
\n
41,273
\n
8,419
\n
49,692
\n
\n
\n
Japan
\n
11,000
\n
34,410
\n
8,600
\n
42,750
\n
7,000
\n
49,000
\n
6,500
\n
55,500
\n
\n
\n
Malaysia
\n
63
\n
231
\n
54
\n
286
\n
50
\n
386
\n
52
\n
438
\n
\n\n
Table 2.
Net solar PV capacity and total addition by country from 2015 to 2018 [10, 11].
\n
Among these four countries, in terms of annual production in 2018 (Figure 2), China has produced the most energy of a figure close to 80 GW. This is followed by Malaysia with an annual production of approximately 15 GW. Subsequently, Japan produced around 5 GW in that year and lastly, the USA has produced half of Japan’s [12].
\n
Figure 2.
Global PV cell production from 2015 to 2018 [12].
\n
\n
\n
2.5 Section conclusion
\n
Based on the trends, the number of solar PV additions by each of the countries has plateaued in recent years due to hurdles faced within the country. Considering this, some other countries have been growing in this field including Malaysia. Ever since the first LSS was developed, the country has been developing more projects that is able to harness the sun’s energy. Due to the country’s accumulative efforts, Malaysia has the potential to become one of the leading countries in solar PV generation given that further research and development is given into this field.
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\n
\n
\n
3. Malaysia hydropower information
\n
\n
3.1 Introduction to hydropower
\n
Hydropower is the conversion of Kinetic Energy (KE) of water into electricity and is considered a RES due to the water cycle being constantly renewed by the sun. According to an article on the US Geological Survey website, a hydropower dam works by having the water in the reservoir flow into a pathway called the penstock when the sluice gate is opened. This penstock is directly connected to the turbine, which is spun by the force of the water moving from a location of higher pressure to one of lower pressure. The water itself then flows out to a river below, whereas the turning of the turbine causes the conversion of KE from the water force into mechanical energy for use by the generator, which is connected to it by way of shafts or gears. This turning of the turbine also causes the rotor within the generator to turn and consequently causes the electromagnets on its edge to move past the stators placed in a static position outside the rotor, allowing for the conversion of the mechanical energy from the turbine into Electrical Energy (EE). The electricity produced from this conversion process is then carried out to other locations and facilities by way of power to transmission lines connected directly to the generator.
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\n
\n
3.2 Hydropower in Malaysia
\n
International Hydropower Association states that the installed hydropower capacity is 6094 MW in 2016, with hydropower generating roughly 11% of the country’s electricity and less than 20% of the technically feasible generation potential utilized to date in their article from May 2017 [14]. The following comparison has been done by choosing the most five powerful Hydropower plants in Malaysia.
\n
\n
3.2.1 Bakun Hydroelectric Plant, Sarawak
\n
The Bakun Hydroelectric Plant is located on Batang Lui in the upper parts of the Rajang River, roughly 37 km upstream of the town of Belaga in Sarawak. The plant is powered by eight 300 MW turbines, allowing for an installed generation capacity of 2400 MW and has a power transmission system that directly connects to the existing power transmission network in Sarawak. The plant has been operational since 2011 and produces an average electricity generation of 1700 MW to 2110 MW depending on demands. The dam is considered to be the largest and tallest Concrete-Faced Rock-fill dam in South East Asia with a 205 m height and 750 m length, with the capability to contain 16.93 million m3 of water, allowing the reservoir a surface area of around 695km2 with a catchment area of 14750 km2 [13].
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\n
\n
3.2.2 Murum Hydroelectric Plant, Sarawak
\n
The Murum Hydroelectric Plant was completed back in 2016 and is located on the Murum River in the upper region of the Rajang River Basin, roughly 200 km from Bintulu. The plant is powered by four 236 MW turbines, which totals to an installed generation capacity of 944 MW [13, 14], with its average production being around 635 MW and would be delivered through the state power grid. The dam is 141 m high and 473 m long, with a reservoir area of 270km2 and a catchment area of 2750km2. The cost of the project totaled about RM 4.8 billion [15]. Besides that, Murum also has the world’s tallest stepped chute spillway that helps to reduce KE by aerating the water overflow, which also helps to preserve the riverine ecosystem and the Batu Tungun rock formation, which is considered sacred to the local Penan community [14].
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\n
\n
3.2.3 Pergau Hydroelectric Station, Kelantan
\n
The Pergau Hydroelectric Station is located on the Pergau Lake, around 100 km away from Kota Bharu, Kelantan. The plant is powered by four 150 MW turbines totaling 600 MW of installed generation capacity and was designed to operate at a daily load factor of 25%. The Kuala Yong dam, which the power station receives its water from, is 75 m high [15, 16], with a 54km2 upper catchment and lower plain area. Besides that, the station also has a \n\n1.5\n×\n\n10\n6\n\n\nm\n3\n\n\n reregulating pond designed to accept peak generation flows and to release them into the river in a controlled manner, which also had a generating cycle of 5.5 hours when at full station output. The cost of the project is totaling to RM 2.23 billion [17].
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\n
\n
3.2.4 Sultan Mahmud Power Station, Terengganu
\n
The Sultan Mahmud Power Station was completed in 1985 and located 55 km southwest of Kuala Terengganu on the Kenyir Lake. The plant is powered by four 100 MW turbines, totaling 400 MW of installed generation capacity, with continuous generation being 165 MW. The dam is 155 m high and 800 m long in crest, with a reservoir area of 369km2 and a catchment area of 1260km2. The water height is around 120 m at minimum capacity and can go up to 153 m when it’s at maximum, with a full supply level of 145 m [16, 17]. The lake itself can store 13.6 billion m2 of water, with its deepest point being 145 m. Besides that, it can also release any excess water flow in the reservoir directly downstream into the Terengganu River.
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\n
\n
3.2.5 Ulu Jelai Hydroelectric Power Plant, Pahang
\n
The Ulu Jelai Hydroelectric Power Plant was completed in 2016 and is located in the Cameron Highlands, Pahang on the Bertam River. The plant is powered by two 186 MW turbines which are placed in an underground plant [18], totaling to 372 MW of installed generation capacity for electricity. The Susu Dam, which is the dam that forms the Susu Reservoir of this hydropower plant, was built using almost 750,000m2 of concrete through the Roller-Compacted Concrete (RCC) method, a very modern way to build such a dam. Said dam is measured to be 88 m high and 460 m long in the crest, with a 0.1km2 catchment area. The total cost of the project was RM 4.2 billion and is expected to reduce 250,000 tons of carbon dioxide equivalent per year by substituting coal or fossil fuel-based generator stations during peak hours, according to a United Nations report [17, 18].
\n
\n
\n
\n
3.3 Comparing the projects
\n
Based on the information gathered here, the five selected hydropower projects can be arranged and compared between each other within the categories of installed generation capacity, dam size, catchment area, reservoir area, and project cost (Table 3) [15, 18].
\n
\n
\n
\n
\n
\n
\n
\n
\n\n
\n
Hydropower Station
\n
Max Power (MW)
\n
Turbine Amount
\n
Dam Dimensions (h x l)
\n
Surface Area (km2)
\n
Catchment Area (km2)
\n
Project Cost ($ Billion)
\n
\n\n\n
\n
Bakun
\n
2400
\n
8 x 300
\n
205 x 750
\n
695
\n
14750
\n
7.3
\n
\n
\n
Murum
\n
944
\n
4 x 236
\n
141 x 473
\n
270
\n
2750
\n
4.8
\n
\n
\n
Pergau
\n
600
\n
4 x 150
\n
75 x ---
\n
54
\n
—
\n
2.23
\n
\n
\n
Sultan Mahmud
\n
400
\n
4 x 100
\n
155 x 800
\n
369
\n
1260
\n
—
\n
\n
\n
Ulu Jelai
\n
372
\n
2 x 186
\n
88 x 460
\n
—
\n
0.1
\n
4.2
\n
\n\n
Table 3.
The data for each of the five selected hydroelectric power plants.
\n
When it comes to total installed generation capacity, the Bakun has the highest of the five at 2400 MW, followed by Murum at 944 MW, Pergau/Sultan Ismail Petra at 600 MW, Sultan Mahmud at 400 MW and lastly Ulu Jelai at 372 MW. The reason behind the high output behind Bakun is not only it’s high number of turbines, but the capacity of 300 MW that each turbine is capable of, which in and off itself is close to rivaling the entire output of the Ulu Jelai station at 372 MW. This makes it the most powerful hydroelectric power plant in Malaysia and the largest power generation facility in Sarawak, as it also supports the Sarawak Corridor of Renewable Energy (SCORE) initiative required for the energy-intensive heavy industries such as the Samajaya Industry Park. In terms of the dam sizes, Bakun has the largest at 205 m high and 800 m long, followed by Sultan Mahmud at 155 m high and 800 m long, Murum at 141 m high and 473 m long, and lastly Ulu Jerai at 88 m high and 460 m long. The length of the Pergau/Sultan Ismail Petra was not given but can be assumed to be the smallest of the five as the height is only 75 m. As for catchment area, which is a land area where water can flow into the plant reservoir [15, 18], the largest is Bakun at 14750km2, followed by Murum at 2750km2, Sultan Mahmud at 1260km2, Pergau at 54km2 and lastly Ulu Jerai at 0.1km2. Ulu Jerai is the smallest of the bunch as it uses the Bertam River, whereas the rest have a larger area to work with as they are built on lakes and other large bodies of water. Out of the five stations, only Bakun, Murum and Sultan Mahmud have a listed reservoir size at 695km2, 270km2 and 369km2 respectively. Having a reservoir allows for the storage of water as conversion fuel for a later date [17], meaning that Bakun has the largest water reserve of them all and thus can use more water to generate more electricity in comparison. When it comes to cost, the most expensive project was Bakun at RM 7.3 billion, Murum at RM 4.8 billion, Ulu Jelai at RM 4.2 billion, and lastly Pergau at RM 2.23 billion, whereas the cost for production of the Sultan Mahmud plant was nowhere to be found but could be assumed to be between Pergau and Murum due to the size being between those two and that it was completed in 1985. The cost of Bakun being the highest is because it uses more turbines that are very powerful in order to produce more power than the rest of the ones on the list combined at peak usage, not to mention the size of the construction project itself.
\n
To wrap this part up, the Bakun Hydroelectric Plant is the best hydroelectric plant available in Malaysia due to the amount of installed generation capacity for electricity that it can provide due to the massive size of the project itself, but such power comes at a great price tag. In comparison, a project such as the Sultan Ismail Power Station or Pergau Hydroelectric Station would be a more feasible one to create in a higher quantity for a developing country such as this due to the lower costs and less space requirement, while still capable of pumping out a respectable amount of electricity for the towns, villages and cities found in this country.
\n
\n
\n
3.4 Comparing hydropower in Malaysia to the World
\n
Malaysia’s annual hydropower energy production is rated at 4.5 Mtoe/year (Megaton of energy per year) [16] with an installed hydropower capacity of 6094 MW and a hydropower usage percentage of 11%. The largest dam or hydropower facility in Malaysia is the Bakun Dam at 2400 MW of installed generating capacity.
\n
\n
\n
\n
\n
\n
\n\n
\n
Country
\n
Annual Energy (Mtoe/year)
\n
Strongest dam & output (MW)
\n
Installed hydropower capacity (MW)
\n
Usage Percentage (%)
\n
\n\n\n
\n
China
\n
96.9
\n
Three Gorges’ Dam (22,500)
\n
341,190
\n
20
\n
\n
\n
Brazil
\n
32.9
\n
Itaipu Dam (14,000)
\n
100,273
\n
64
\n
\n
\n
Canada
\n
32.3
\n
Robert-Bourassa Dam (5,616)
\n
79,323
\n
62
\n
\n
\n
Malaysia
\n
4.5
\n
Bakun Dam (2,400)
\n
6,094
\n
11
\n
\n\n
Table 4.
Data for three of the world’s leading hydropower countries in comparison to Malaysia’s.
\n
From the information gathered here, the leading hydropower nations were China, Brazil, and Canada, with 96.9 Mtoe/year, 32.9 Mtoe/year and 32.3 Mtoe/year (megaton of energy per year) respectively, whereas overall energy input from hydropower in Malaysia is totalled to be 4.5 Mtoe/year (kiloton of energy per year). In comparison to the 3 countries stated previously, Malaysia’s hydropower energy input is extremely tiny in comparison (Table 4). When it comes to the respective strongest dams in terms of output, China’s Three Gorges Dam is the highest at 22.5GW of installed generating capacity, followed by the joint Brazil/Paraguay Itaipu Dam at 14GW and lastly Canada’s Robert-Bourassa Dam at 5616 MW. Malaysia’s largest one, Bakun at 2400 MW, is respectable and considered the largest in South-East Asia [13, 17], but the output is nothing compared to these giants. It is generally more than enough for providing electricity to Sarawak itself and can support the local heavy industries found in the state. When it comes to percentages of hydropower usage for electricity in a country, Brazil has the largest at 64%, followed by Canada at 62%, China at 20%, and lastly Malaysia at 11%. Malaysia’s percentage of hydropower usage is lower compared to these other countries as Malaysia still relies heavily on coal for most of their power stations [15], which should be changed as soon as possible as it’s a non-RES and could dry up in the future. In terms of installed hydropower capacity, China is the largest at 341,190 MW, followed by Brazil at 100,273 MW, Canada at 79,323 MW and lastly Malaysia at 6094 MW. Considering how small Malaysia is compared to all the three countries above, it’s understandable that the installed hydropower capacity is far lower than them as Malaysia has much less space and water bodies to work with in comparison, while not to mention Malaysia’s economy not being as strong as them (Figure 3).
\n
Figure 3.
Hydropower Major projects in Malaysia. (a) Bakun Hydropower, (b) Murum Hydropower, (c) Yong Hydropower and (d) Kenyir Hydropower.
\n
\n
\n
3.5 Section conclusion
\n
Taking an example out of Canada or Brazil here would be a good idea as there are many rivers and water bodies that could be exploited for hydroelectricity generation, however building more mega-dams like Bakun could harm the rainforests and animal species that makeup country’s ecosystem, not to mention potentially displacing the natives and eating large sums of money that could be used for other equally beneficial projects. Therefore, a balanced method of implementing hydropower while maintaining the ecosystem should be explored, so that Malaysia could progress to the future with hydropower while still maintaining the well-being of Malaysia’s unique ecosystem.
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\n
\n
\n
4. Malaysia biomass energy information
\n
\n
4.1 Introduction to biomass energy
\n
Biomass is a type of fuel developed from organic materials. It is both sustainable and renewable in terms of generating EE. The organic materials are obtained from living and recently living things. These materials can include scraps of lumber, manure and forest debris. Biomass power is able to generate electricity which is carbon neutral through renewable organic waste [19]. This energy releases heat when burnt. These energies are utilized through burning them to produce steam to run turbines which in turn generates electricity.
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\n
\n
4.2 Biomass in Malaysia
\n
\n
4.2.1 Biomass resources in Malaysia
\n
Malaysia is a country filled with many conventional energy resources. These energy sources include oil and gas which are non-renewable and RESs like solar, hydro and biomass energy. For biomass, Malaysia has plenty of opportunities as far as exploiting biomass energy in Malaysia. Malaysia is filled with agricultural biomass and wood waste which can be exploited and used to replace non –RESs in use [19].
\n
\n
\n
4.2.2 Palm oil biomass
\n
Malaysia’s exporting of 19.9 million tons of palm oil in 2017 makes this country a world leader as an exporter of palm oil. In 2011, the country was able to generate more than 80 million tons of oil palm biomass. 30% of the 379 palm oil mills here in Malaysia utilize palm oil mill effluent (POME) by turning it to biogas [19].
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\n
\n
4.2.3 Rice husk
\n
Another important agricultural biomass is rice husk. This resource has a very good potential for biomass cogeneration. Biomass cogeneration refers to “generating together”, this is a process where heat and EE is obtained at the same time from fuel. This type of biomass is implemented in technologies such as steam turbines, gas turbines and reciprocating engines. Currently, Malaysia has constructed its first rice husk power plant in the state of Kedah in Padang [19, 20].
\n
\n
\n
4.2.4 Municipal solid wastes
\n
For the generation of solid waste in Malaysia, the amount of mass-produced in a day range from 0.45–1.44 kg/day. This result is dependent on the economic status of the area within Malaysia. The organic waste in Malaysia contains a high amount of moisture with a bulk density of above 200 kg/m3. The bulk density is with respect to the population growth in Malaysia, the higher the number of populations in the area the larger the bulk density of the waste. These waste are generally disposed of as landfilling which makes them ideal for being used for biomass [20] (Figure 4).
\n
Figure 4.
Electricity generation by fuel and Power generation sources in Malaysia.
\n
\n
\n
\n
4.3 Biomass projects in Malaysia
\n
\n
4.3.1 TSH resources Berhad
\n
The plant has huge commercial potential from its biowaste in the palm oil industry. It does this through an integrated complex system in Kunak, Tawau situated in east Malaysia, Sabah. This plant has both biomass and biogas power plants as well as being equipped with a pulp and paper plant. The plant is considered friendly to the environment as it takes into consideration the protection and preservation of the environment. This plant is responsible for the generation of electricity through the disposal of waste from oil palms. This plant is under the ownership of the Kumpulan Sawit Kinabalu and has taken considerable precautions in order to create a sustainable wealth while ensuring the protection and preservation of the environment. The amount of energy production has dropped by nearly 85% since the opening of the power plant, and as a result, increasing the profit of the mills by RM1.14 million [21]. The power generation of the plant is 14 MW of completely RE from biomass cogeneration plant [21]. The plant is also the first biomass power plant connected to the main grid in Malaysia. The RE from the biomass power plant has formed an agreement with the Sabah Electricity Sdn Bhd to provide green electricity of up to 10 MW [20, 22]. TSH built up approximately 50,000 ha in a planted area across Sabah which are strategically located with associated companies. The company also has 65,000 ha worth of unplanted land bank for future development, this is to keep the company busy for many years to come. In addition to that, the company also has 3 mills in Sabah which has a 1.0 million tons of Fresh Fruit Bunches processing capacity per annum. The refining crude palm oil and kernel located at Kunak Jaya, Sabah has capacities of 2600 tons and 600 tons per day respectively [21, 22].
\n
\n
\n
4.3.2 Seguntor bioenergy and Kina biopower biomass power plant
\n
Both these power plants are in Sandakan, Sabah. Seguntor Bioenergy and Kina Biopower Power Plant are owned by HRE Seguntor Bioenergy Sdn. Bhd and HRE Kina Biopower Sdn. Bhd respectively [23]. These two power plants are implemented with a similar design. The power plants have a fuel consumption of 23.123 kg/h and a boiler capacity of 56 tons per hour at 420 degrees Celsius. Adding to that, a mechanical draught cooling tower, counterflow, water flow of around 2491 t/h. The coldwater temperature is measured at 32 degree Celsius and 42 degree Celsius for the hot water temperature. The generators are enclosed and has an in –built water – air-cooled system. A synchronous generator is also used in the system. Each power plant can provide a total of 11.5 MW of green energy from biomass energy [23, 24]. These efforts are made to ensure the provision of a stable power supply to consumers in the East Coast of Malaysia. The power plants are located strategically about 20–90 km to 15 palms oi mills. Furthermore, the power plants are located 10 km radii of SESB’s substation making it ideal for grid interconnection [20, 23]. About 654,000 tonnes per year of biomass will be generated from the Nilai Tani Resources Sdn. Bhd., Monsok Palm Oil Mill Sdn. Bhd, Prolific Yield Sdn. Bhd. and Tanjung Panjang Sdn. Bhd palm oil mills. The power plants are expected to cost around RM120 million each.
\n
\n
\n
4.3.3 Jana Landfill
\n
The Jana Landfill is owned by the Jana Landfill Sdn Bhd which runs a power plant and municipal storage waste sites. It is a subsidiary of TNB Energy Services. The power plant is located in Ayer Hitam Forest Reserve in Puchong, Selangor. The Jana Landfill obtains its fuel via the decomposition of natural municipal waste from the landfill site. The power plant generates a total of 2 MW of green energy using landfill gas as a fuel source [21, 24]. The power plant has two separate sections, Jana 1 and Jana 2. Each power plant can generate up to 1 MW of energy. To date with the arrival of Jana 3, the power plants is expected to generate a combined total of 6 MW which is beneficial to about 6000 homes in Malaysia.
\n
\n
\n
4.3.4 Recycle energy Sdn. Bhd
\n
The Recycle Energy power plant is the first power in the whole of Southeast Asia to initiate Refuse Derived Fuel (RDF). RDF is the product of separating noncombustible and combustible portion from municipal solid waste. This method can help increase the recycling levels in Malaysia as well as decrease the overall waste. To add to this, this method does not require additional cost from processing, baling, wrapping and transportation logistics making it less expensive than that of the landfilling [25]. RDF can be used as a renewable fuel for any coal – fired power plant. Recycle Energy power plant is located at Kampung Pasir in Semenyih, Selangor. The plant is located about 13 miles from the main capital. This facility is able to process a total of 1100 tons of solid waste a day. These wastes are then converted into RDF which is in fluff form. The RDF in fluff form is used as biofuel to enable the production of 8 MW of electrical energy a day [24, 25]. This electricity is used to power up the RDF plant and any remaining electricity is sold for usage in the national power grid. The RDF power plant is 28 – acre wide and is handled by the Malaysian government (Figure 5).
\n
Figure 5.
Major biomass projects in Malaysia.
\n
\n
\n
\n
4.4 Comparison between the biomass energy usages in different plants in Malaysia
\n
When compared, the TSH Resources Berhad power plant located in Kunak, Tawau in Sabah has the highest power generation at 14 MW. The main reason for the success of the TSH Resources Berhad power plant is its immense area of coverage. Palm oil is able to be attained from the within the power plants location. Continues supplies of palm waste can be obtained and processed rapidly in the power plant. The Kumpulan Sawit Kinabalu also ensures the protection and preservation of the palm oil farms. The Seguntor and Kina power plants needs to transport its oil palm waste 20–90 km from the mills to the power plants thus having a lower efficiency rate compared to the TSH Resources power plant. Furthermore, the TSH Resources Berhad power plant uses a biomass cogeneration system enabling it to attain both electrical and heat energy from the biomass fuels (Table 5).
\n
\n
\n
\n
\n
\n
\n
\n\n
\n
Power Plants
\n
Power generation
\n
Type of Turbine
\n
Fuel
\n
Cost
\n
Area coverage
\n
\n\n\n
\n
TSH Resources Berhad
\n
14 MW
\n
Steam turbines
\n
Empty fruit bunch
\n
\n
5e+8 square meter (used land) and 6.5e+8 (unused land)
\n
\n
\n
Seguntor Bioenergy Power Plant
\n
11.5 MW
\n
Steam turbines
\n
Empty fruit bunch
\n
RM120 million
\n
400000 square meters
\n
\n
\n
Kina Biopower Power Plant
\n
11.5 MW
\n
Steam turbines
\n
Empty fruit bunch
\n
RM120 million
\n
400000 square meters
\n
\n
\n
Jana Landfill
\n
2 MW (From Jana 1 & 2), 6 MW (with the future addition of Jana 3)
\n
Gas turbines
\n
Biogas
\n
\n
\n
\n
\n
Recycle Energy power plant
\n
8 MW
\n
Steam turbines
\n
Refuse-derived fuel
\n
\n
113312 square meters
\n
\n\n
Table 5.
Comparison between the biomass energy of different power plants in Malaysia.
\n
In terms of the turbines used, steam engine has a better power-to-weight ratio making them ideal for reciprocating engines. For a small size is able to generate a high amounts of power output and does not produce a lot of vibration compared to other reciprocating counterparts. The steam turbine has a higher operating efficiency and reliability compared to that of the gas turbines. Jana Landfill is the only power plant in Malaysia using gas turbines and from power generation it is the lowest compared to all the other power plants which are using steam turbines. A main issue is that, having variation in its fuel specs can lead to an enormous drop in the efficiency of the turbine. In addition to that, external power is required to ensure turbine can carry out a self-sustained operation [23, 26]. In terms of the most eco-friendly fuel source would be the source used by the Recycle Energy power plant. This power plant uses a refuse-derived fuel source making it ideal to not only for making biofuels to power up turbines inside the power plant, but also recycling resources which are not combustibles.
\n
From the comparison table, it can be seen that in terms of practicality and usage in the whole Malaysia the TSH Resources Berhad power plant is the most ideal. It is able to generate the highest amounts of the greenest EE at 14 MW which is why it is connected to the main grid in East Malaysia.
\n
\n
\n
4.5 Comparison between the usages of biomass energy in Malaysia against the World
\n
Unlike the other countries, Malaysia is highly reliant on the usage of palm oil and coconut husk as biomass sources. Malaysia is still unable to completely utilize all resources which can lead to the production of biomass. If Malaysia can utilize converting municipal waste as a source for biomass, there is no reason to why Malaysia cannot increase their power generation from biomass. In addition to that, if Malaysia is able to produce more biomass power plants situated around palm oil fields like the TSH Resources Berhad power plant, the amount of power generated from biomass is bound to increase within the country (Table 6).
\n
\n
\n
\n
\n
\n
\n\n
\n
Country
\n
Power generation from biofuels (GWh)
\n
Source of waste
\n
\n
\n
2014
\n
2015
\n
2016
\n
\n\n\n
\n
America
\n
62357
\n
61640
\n
60493
\n
Wood waste, agricultural crop, animal manure, plants and recycled waste
\n
\n
\n
China
\n
44400
\n
52700
\n
64700
\n
Agricultural, forestry waste and domestic livestock (manure).
\n
\n
\n
India
\n
293926
\n
24997
\n
41972
\n
Agricultural wastes.
\n
\n
\n
Malaysia
\n
701
\n
751
\n
760
\n
Palm oil biomass, rice husk and municipal solid waste.
\n
\n\n
Table 6.
Comparison between the amounts of electricity generation from biomass between countries.
\n
\n
\n
4.6 Section conclusion
\n
Malaysia is still relatively new in terms of the power generation using biomass sources. From the year 2014–2016 there is a gradual increase in the power generation using biofuels in Malaysia. Thus. the potential is bright for the usage of biomass as a RESs in Malaysia.
\n
\n
\n
\n
5. Malaysia tidal energy information
\n
\n
5.1 Introduction to tidal energy
\n
Tides are created from the gravitational pull from the Earth and the moon, creating coastal tidal waters at a different time at the day. This movement of water has an enormous amount of potential energy. This energy is predictable and renewable with low operating cost. Although tidal energy is recognized as one of the promising technologies, the technology currently doesn’t exist in Malaysia. There are three main types of tides phenomenon which are diurnal, semidiurnal and mixed tides [27]. Diurnal tides have one high tide every day. Semidiurnal tides have two high tides every day. Mixed tides are the combination of the characteristics of diurnal and semidiurnal tides. Tidal energy can be harnessed through different methods. A tidal barrage makes use of the tides. A barrage looks like a dam, but it’s lesser height and very much bigger [28]. The other method would be the tidal stream. It works just like wind turbines, but it’s placed underwater using the movement of water created by tides [27, 28]. A tidal lagoon is another method similar to the tidal barrage, but the dam is replaced by a 360-degree enclosure, creating a pool. Water will enter and exit the lagoon due to different water tides.
\n
\n
\n
5.2 Feasibility of tidal energy in Malaysia
\n
To determine the feasibility of tidal energy in Malaysia, it is required to understand the available tides in Malaysia. In Malaysia, there is no diurnal tides. The North and West of Peninsula have majority of semidiurnal tides while the area of South and East have majority of mixed tides with dominant semidiurnal. The rest of the area of Malaysia has mixed tides with dominant diurnal (Figure 6).
\n
Figure 6.
Types of tides available in Malaysia [29].
\n
The tides differ at a different location and different times of the year. The height of water level between tides also influences the potential energy that could be harnessed. As shown in the below figure, the most potential location to harness tidal energy would be Selangor with height range between 0.4 meters to 5.3 meters when compared to other locations [28, 29].
\n
\n
\n
5.3 Section conclusion
\n
The tidal energy will always be influenced by the gravity of the moon and the sun. However, it has more advantages than wind and solar energy as it has a more predictable nature with high environmental benefits. Different locations in Malaysia have different tides and it must be considered before installing a tidal power plant. Based on the analysis being done, Selangor has the highest potential to harness tidal energy compared to other locations in Malaysia (Figure 7).
\n
Figure 7.
Semidiurnal and Dominant semidiurnal Tides.
\n
\n
\n
\n
6. Malaysia geothermal energy information
\n
\n
6.1 Introduction to geothermal energy
\n
Geothermal energy is created by the gravitational energy of the Earth and the unstable radioactive decay of atoms [29]. Geothermal energy is mainly used to generate electricity and to provide heating. Although geothermal energy technologies have been around for over 40 years, they are still undergoing research and development. This is due to the complexity and high investments before executing geothermal projects as it includes underground exploration and requires multidisciplinary expertise [30] (Figure 8).
\n
Figure 8.
How geothermal energy works.
\n
\n
\n
6.2 Feasibility of geothermal energy in Malaysia
\n
Malaysia does not have technology that harnesses geothermal energy. However, there are several potential locations in Malaysia.
\n
According to a study by the Deputy Natural Resources and Environment of Malaysia back in 2010, Tawau has the potential to generate up to 67 MW of electricity per day, meeting the demands of Tawau [1, 31]. The water temperatures below the selected area are near to 235 degrees which is more than enough to heat and at the same time generate electricity. This geothermal project was initiated in Tawau, Sabah, Malaysia back in 2015. However, the project site has not shown any progress and had seemed to stop operations in the third quarter of 2016. Therefore, the project’s approval is being cancelled and is now currently abandoned [29, 31] (Figure 9).
\n
Figure 9.
Tawau geothermal project being abandoned.
\n
\n
\n
6.3 Section conclusion
\n
The feasibility of geothermal energy in Malaysia is inclusive of geothermal exploration and resource assessment, which requires a very high cost. The country’s first geothermal power plant project failed due to the lack of preparation and great deal of discipline in executing the project. Based on the history of geothermal development, the geothermal project can easily go wrong if not all aspects are addressed adequately.
\n
\n
\n
\n
7. Conclusion
\n
Malaysia is a developing country and being able to harness RE would be a great attribute to improve the country. The existing RE in Malaysia includes Solar energy, Hydropower energy, and Biomass energy. Other potential REs in Malaysia could be harvested such as Tidal energy. Solar cells are commonly used to harness solar energy. The technology can be further investigated and improved to increase the efficiency of electricity generation. Hydropower in Malaysia is generating 11% of the country’s electricity as Malaysia has many rivers and water bodies that could be exploited. A balanced method of implementing hydropower can be done to always ensure the ecosystem of Malaysia is not disturbed. Malaysia is still relatively new in using Biomass energy. However, the gradual increase of power generation using biofuels has increased the potential of biomass energy in Malaysia as a renewable energy source. Tidal energy has the potential to be harnessed in Malaysia as there are locations such as Selangor and Johor having tides that could generate a decent amount of electricity. Geothermal energy also has the potential in Malaysia as there are multiple hot springs. Sabah has the potential to harness geothermal energy as it originates within young volcanic area. However, more research and investment would be needed to harness geothermal energy in Malaysia. It is quite convincing that Malaysia could harness more RE as the sustainability of energy consumption is crucial in this era.
\n
\n\n',keywords:"Malaysia, renewable energy, solar energy, hydropower, biomass, geothermal",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/75754.pdf",chapterXML:"https://mts.intechopen.com/source/xml/75754.xml",downloadPdfUrl:"/chapter/pdf-download/75754",previewPdfUrl:"/chapter/pdf-preview/75754",totalDownloads:34,totalViews:0,totalCrossrefCites:0,dateSubmitted:"September 24th 2020",dateReviewed:"February 12th 2021",datePrePublished:"March 16th 2021",datePublished:null,dateFinished:"March 16th 2021",readingETA:"0",abstract:"Malaysia is one of the fastest emerging and developing countries in the world. To drive the economical workhorse, large amounts of power is required. The power demand has risen to 156,003 GWh per year in the year 2016, almost 30,000 GWh more than 5 years prior. Fossil fuels such as natural gas, coal, oil, and diesel have been the driving force powering Malaysia’s grids. However, these resources will not last forever, and they do harm to our environment. To counter this, renewable energy (RE) projects have been constructed all around Malaysia. This paper discusses on available and existing renewable energy systems (single/hybrid) in Malaysia and provides a comparison of their electricity generation capabilities. The renewable energy sources that are covered in this paper include Solar, Hydropower, Biomass, Tidal and Geothermal. At the moment, hydropower is the largest renewable energy producer, contributing to almost 15% of the country’s total energy generation. A lot of resources have been channeled towards the initiative of hydropower and it has definitely borne much fruit. This is followed by Solar Energy. Even though it is not as successful as hydropower, there is still a lot of avenues for it to grow in a tropical country like this. Malaysia is still relatively new in terms of power generation using biomass sources. There has been a gradual increase in the power generation using biofuels through the years and its future does look bright. Energy generation from wind, tidal, and geothermal sources has been rather challenging. Because of Malaysia’s geographical location, it experiences slow winds on average throughout the year. This has led to insufficient output for its financial input. Besides that, Malaysia also has relatively low tide, if compared to other Asian countries such as Indonesia and the Philippines. This contributed to the failure of tidal energy in Malaysia, but there have been signs of locations that can be suitable for this energy generation. Besides that, the country’s first geothermal power plant project failed due to a lack of preparation and discipline during the project’s execution. There is a high initial cost for geothermal projects, and the chances of failure are high if the necessary precautions are not followed. This could be one of the reasons why this branch of renewable energy has not been explored deeply.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/75754",risUrl:"/chapter/ris/75754",signatures:"Hadi Nabipour Afrouzi, Yuhani Pamodha Wimalaratna, Jubaer Ahmed, Kamyar Mehranzamir, San Chuin Liew, Chin-Leong Wooi and Bazlul Mobin Siddiquea",book:{id:"10457",title:"Entropy and Exergy in Renewable Energy",subtitle:null,fullTitle:"Entropy and Exergy in Renewable Energy",slug:null,publishedDate:null,bookSignature:"Prof. Lin-Shu Wang",coverURL:"https://cdn.intechopen.com/books/images_new/10457.jpg",licenceType:"CC BY 3.0",editedByType:null,isbn:"978-1-83968-663-4",printIsbn:"978-1-83968-662-7",pdfIsbn:"978-1-83968-664-1",editors:[{id:"223830",title:"Prof.",name:"Lin-Shu",middleName:null,surname:"Wang",slug:"lin-shu-wang",fullName:"Lin-Shu Wang"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:null,sections:[{id:"sec_1",title:"1. Introduction to renewable energies",level:"1"},{id:"sec_2",title:"2. Malaysia solar energy information",level:"1"},{id:"sec_2_2",title:"2.1 Introduction to solar energy",level:"2"},{id:"sec_3_2",title:"2.2 Solar energy in Malaysia",level:"2"},{id:"sec_3_3",title:"2.2.1 Pajam, Negeri Sembilan",level:"3"},{id:"sec_4_3",title:"2.2.2 Mukim Tanjung 12, Kuala Selangat, Selangor",level:"3"},{id:"sec_5_3",title:"2.2.3 Sungai Siput, Perak",level:"3"},{id:"sec_6_3",title:"2.2.4 Kudat, Sabah",level:"3"},{id:"sec_8_2",title:"2.3 Comparing the projects",level:"2"},{id:"sec_9_2",title:"2.4 Comparing solar energy in Malaysia to the World",level:"2"},{id:"sec_10_2",title:"2.5 Section conclusion",level:"2"},{id:"sec_12",title:"3. Malaysia hydropower information",level:"1"},{id:"sec_12_2",title:"3.1 Introduction to hydropower",level:"2"},{id:"sec_13_2",title:"3.2 Hydropower in Malaysia",level:"2"},{id:"sec_13_3",title:"3.2.1 Bakun Hydroelectric Plant, Sarawak",level:"3"},{id:"sec_14_3",title:"3.2.2 Murum Hydroelectric Plant, Sarawak",level:"3"},{id:"sec_15_3",title:"3.2.3 Pergau Hydroelectric Station, Kelantan",level:"3"},{id:"sec_16_3",title:"3.2.4 Sultan Mahmud Power Station, Terengganu",level:"3"},{id:"sec_17_3",title:"3.2.5 Ulu Jelai Hydroelectric Power Plant, Pahang",level:"3"},{id:"sec_19_2",title:"3.3 Comparing the projects",level:"2"},{id:"sec_20_2",title:"3.4 Comparing hydropower in Malaysia to the World",level:"2"},{id:"sec_21_2",title:"3.5 Section conclusion",level:"2"},{id:"sec_23",title:"4. Malaysia biomass energy information",level:"1"},{id:"sec_23_2",title:"4.1 Introduction to biomass energy",level:"2"},{id:"sec_24_2",title:"4.2 Biomass in Malaysia",level:"2"},{id:"sec_24_3",title:"4.2.1 Biomass resources in Malaysia",level:"3"},{id:"sec_25_3",title:"4.2.2 Palm oil biomass",level:"3"},{id:"sec_26_3",title:"4.2.3 Rice husk",level:"3"},{id:"sec_27_3",title:"4.2.4 Municipal solid wastes",level:"3"},{id:"sec_29_2",title:"4.3 Biomass projects in Malaysia",level:"2"},{id:"sec_29_3",title:"4.3.1 TSH resources Berhad",level:"3"},{id:"sec_30_3",title:"4.3.2 Seguntor bioenergy and Kina biopower biomass power plant",level:"3"},{id:"sec_31_3",title:"4.3.3 Jana Landfill",level:"3"},{id:"sec_32_3",title:"4.3.4 Recycle energy Sdn. Bhd",level:"3"},{id:"sec_34_2",title:"4.4 Comparison between the biomass energy usages in different plants in Malaysia",level:"2"},{id:"sec_35_2",title:"4.5 Comparison between the usages of biomass energy in Malaysia against the World",level:"2"},{id:"sec_36_2",title:"4.6 Section conclusion",level:"2"},{id:"sec_38",title:"5. Malaysia tidal energy information",level:"1"},{id:"sec_38_2",title:"5.1 Introduction to tidal energy",level:"2"},{id:"sec_39_2",title:"5.2 Feasibility of tidal energy in Malaysia",level:"2"},{id:"sec_40_2",title:"5.3 Section conclusion",level:"2"},{id:"sec_42",title:"6. Malaysia geothermal energy information",level:"1"},{id:"sec_42_2",title:"6.1 Introduction to geothermal energy",level:"2"},{id:"sec_43_2",title:"6.2 Feasibility of geothermal energy in Malaysia",level:"2"},{id:"sec_44_2",title:"6.3 Section conclusion",level:"2"},{id:"sec_46",title:"7. Conclusion",level:"1"}],chapterReferences:[{id:"B1",body:'\nN. H. M Binti Tambi, H. N. Afrouzi, K. 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Available: http://dspace.unimap.edu.my/dspace/bitstream/123456789/40810/1/A renewable power source- visit to amcorp gemas solar power plant.pdf.\n'},{id:"B11",body:'\nG. Masson and M. Brunisholz, “2015 Snapshot of global photovoltaic markets,” Iea Pvps T1–292016, pp. 1–19, 2016, [Online]. Available: http://www.iea-pvps.org/fileadmin/dam/public/report/PICS/IEA-PVPS_-__A_Snapshot_of_Global_PV_-_1992-2015_-_Final_2_02.pdf.\n'},{id:"B12",body:'\nA. Jäger-Waldau, “Snapshot of photovoltaics-February 2020,” Energies, vol. 13, no. 4, 2020, doi: 10.3390/en13040930.\n'},{id:"B13",body:'\nM. Hossain et al., “A state-of-the-art review of hydropower in Malaysia as renewable energy: Current status and future prospects,” Energy Strateg. Rev., vol. 22, no. November, pp. 426–437, 2018, doi: 10.1016/j.esr.2018.11.001.\n'},{id:"B14",body:'\nMalaysia Energy Commission, “National Energy Balance 2016,” Energy Comm., pp. 1–114, 2018, [Online]. Available: www.st.gov.my.\n'},{id:"B15",body:'\nA. Kadier, M. S. 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September 2018, pp. 239–249, 2019, doi: 10.1016/j.enpol.2019.02.036.\n'},{id:"B19",body:'\nS. M. Shafie, T. M. I. Mahlia, H. H. Masjuki, and A. Ahmad-Yazid, “A review on electricity generation based on biomass residue in Malaysia,” Renew. Sustain. Energy Rev., vol. 16, no. 8, pp. 5879–5889, 2012, doi: 10.1016/j.rser.2012.06.031.\n'},{id:"B20",body:'\nM. D. M. Samsudin and M. M. Don, “Municipal solid waste management in Malaysia: Current practices, challenges and prospect,” J. Teknol. Sciences Eng., vol. 62, no. 1, pp. 95–101, 2013, doi: 10.11113/jt.v62.1293.\n'},{id:"B21",body:'\nY. H. Chan et al., “An overview of biomass thermochemical conversion technologies in Malaysia,” Sci. Total Environ., vol. 680, pp. 105–123, 2019, doi: 10.1016/j.scitotenv.2019.04.211.\n'},{id:"B22",body:'\nS. H. Shuit, K. T. Tan, K. T. Lee, and A. H. Kamaruddin, “Oil palm biomass as a sustainable energy source: A Malaysian case study,” Energy, vol. 34, no. 9, pp. 1225–1235, 2009, doi: 10.1016/j.energy.2009.05.008.\n'},{id:"B23",body:'\nZ. Haryati, S. K. Loh, S. H. Kong, and R. T. Bachmann, “Pilot scale biochar production from palm kernel shell (PKS) in a fixed bed allothermal reactor,” J. Oil Palm Res., vol. 30, no. 3, pp. 485–494, 2018, doi: 10.21894/jopr.2018.0043.\n'},{id:"B24",body:'\nM. S. Umar, P. Jennings, and T. Urmee, “Generating renewable energy from oil palm biomass in Malaysia: The Feed-in Tariff policy framework,” Biomass and Bioenergy, vol. 62, pp. 37–46, 2014, doi: 10.1016/j.biombioe.2014.01.020.\n'},{id:"B25",body:'\nC. Nobre, O. Alves, L. Durão, A. Şen, C. Vilarinho, and M. Gonçalves, “Characterization of hydrochar and process water from the hydrothermal carbonization of Refuse Derived Fuel,” Waste Manag., vol. 120, pp. 303–313, 2021, doi: 10.1016/j.wasman.2020.11.040.\n'},{id:"B26",body:'\nJ. Zueco, D. López-Asensio, F. J. Fernández, and L. M. López-González, “Exergy analysis of a steam-turbine power plant using thermocombustion,” Appl. Therm. Eng., vol. 180, no. July, p. 115812, 2020, doi: 10.1016/j.applthermaleng.2020.115812.\n'},{id:"B27",body:'\nN. A. Mohd Yusoff, N. L. Ramli, and M. R. Mohamed, “Investigation of the potential harnessing tidal energy in Malaysia,” ARPN J. Eng. Appl. Sci., vol. 10, no. 21, pp. 9835–9841, 2015.\n'},{id:"B28",body:'\nA. L. Maulud and H. Saidi, “The Malaysian Fifth Fuel Policy: Re-strategising the Malaysian Renewable Energy Initiatives,” Energy Policy, vol. 48, pp. 88–92, 2012, doi: 10.1016/j.enpol.2012.06.023.\n'},{id:"B29",body:'\nS. E. Ben Elghali, R. Balme, K. Le Saux, M. El Hachemi Benbouzid, J. F. Charpentier, and F. Hauville, “A simulation model for the evaluation of the electrical power potential harnessed by a marine current turbine,” IEEE J. Ocean. Eng., vol. 32, no. 4, pp. 786–797, 2007, doi: 10.1109/JOE.2007.906381.\n'},{id:"B30",body:'\nJ. W. Lund and A. N. Toth, “Direct utilization of geothermal energy 2020 worldwide review,” Geothermics, vol. 90, no. July 2020, p. 101915, 2021, doi: 10.1016/j.geothermics.2020.101915.\n'},{id:"B31",body:'\nM. B. Farriz, A. N. Azmi, N. A. M. Said, A. Ahmad, and K. A. Baharin, “A study on the wind as a potential of renewable energy sources in Malaysia,” ECTI-CON\n2010\n–2010 ECTI Int. Conf. Electr. Eng. Comput. Telecommun. Inf. Technol., pp. 651–655, 2010.\n'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Hadi Nabipour Afrouzi",address:"hafrouzi@swinburne.edu.my",affiliation:'
Faculty of Engineering, Computing and Science, Swinburne University of Technology Sarawak, Malaysia
Faculty of Engineering, Computing and Science, Swinburne University of Technology Sarawak, Malaysia
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The full content of chapters can be read, copied and printed from the link location of the chapter and these actions are not limited or restricted in any way.
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Registration is requested only to download the PDF of the chapter. There are no subscription fees and there is no charge to user groups.
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IntechOpen chapters are distributed under CC BY 3.0 licences allowing users to “copy, use, distribute, transmit and display the work publicly and to make and distribute derivative works, in any digital medium for any responsible purpose, subject to proper attribution of authorship...” and there is no non-commercial restriction.
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