In this chapter, it is demonstrated that when using advanced evolutionary algorithms, whatever the adopted system model (SOSPD, nonminimum phase, oscillatory or nonlinear), it is possible to find optimal parameters for PID controllers satisfying simultaneously the behavior of the system and a performance index such as absolute integral error (IAE). The Multidynamics Algorithm for Global Optimization (MAGO) is used to solve the control problem with PID controllers. MAGO is an evolutionary algorithm without parameters, with statistical operators, and for the optimization, it does not need the derivatives, what makes it very effective for complex engineering problems. A selection of some representative benchmark systems is carried out, and the respectively two-degree-of-freedom (2DoF) PID controllers are tuned. A power electronic converter is adopted as a case study and based on its nonlinear dynamical model, a PI controller is tuned. In all cases, the control problem is formulated as a constrained optimization problem and solved using MAGO. The results found are outstanding.
Part of the book: PID Control for Industrial Processes
This chapter presents a procedure to design and control power electronic converters (PECs), which includes a zero-based analysis as a dynamical system response criterion for dimensioning converter passive elements. For this purpose, a nonideal boost DC-DC converter (converter considering its parasitic losses) is dynamically modeled and analyzed in steady state as an application example. The steady-state model is obtained from the average nonlinear model. The steady-state model allows deducing expressions for equilibrium conversion ratio M D and efficiency η of the system. Conditions for the converter conduction modes are analyzed. Simulations are made to see how parasitic losses affect both M D and η . Then, inductor current and capacitor voltage ripple analyses are carried out to find lower boundaries for inductor and capacitor values. The values of the boost DC-DC converter passive elements are selected taking into account both steady-state and zero-based analyses. A nonideal boost DC-DC converter and a PI-based current mode control (CMC) structure are designed to validate the proposed procedure. Finally, the boost DC-DC converter is implemented in PSIM and system operating requirements are satisfactorily verified.
Part of the book: Applied Modern Control
In developing countries, rural electrification in areas with limited or no access to grid connection is one of the most challenging issues for governments. These areas are partially integrated with the electrical grid. This poor electricity distribution is mainly due to geographical inaccessibility, rugged terrains, lack of electrical infrastructure, and high required economic investment for installing large grid-connected power lines over long distances to provide electricity for regions with a low population. On the other hand, rapid depletion of fossil fuel resources on a global scale and progressive increase of energy demand and fuel price are other motives to reduce the reliance on fossil fuels. Hybrid renewable energy system (HRES) can be a suitable option for such remote areas. The objective of this chapter is to develop a methodology for sizing hybrid power generation systems (solar-diesel), battery-backed in non-interconnected zones, which minimizes the total cost and maximizes the reliability of supply using particle swarm optimization (PSO). The proposed methodology assists the sizing and designing process of an HRES for an off-grid area minimizing the cost of energy (COE) and maximizing the reliability of the system. Economic incentives offered by the Colombian government are considered in the model.
Part of the book: Wind Solar Hybrid Renewable Energy System