Abstract
Considering gantry cable as an elastic string having a distributed mass, we constitute a dynamic model for coupled flexural overhead cranes by using the extended Hamilton principle. Two kinds of nonlinear controllers are proposed based on the Lyapunov stability and its improved version entitled barrier Lyapunov candidate to maintain payload motion in a certain defined range. With such a continuously distributed model, the finite difference method is utilized to numerically simulate the control system. The results show that the controllers work well and the crane system is stabilized.
Keywords
- overhead cranes
- finite difference method
- Lyapunov stability
- distributed modeling
1. Introduction
Nowadays, cargo transportation plays an important role in many industrial fields. For carrying the cargo in short distance or small area, such as in automotive factories and shipyards, the overhead cranes are naturally applied. To increase productivity, the overhead cranes today are required in high-speed operation. However, the fast motion of overhead cranes usually leads to the large swings of cargo and non-precise movements of trolley and bridge. The faster the cargo transport is, the larger the cargo swings. This makes dangerous and unsafe situation during the operating process. The crane itself and the concerning equipment in the factory can be damaged without proper control strategies.
In recent decades, the control problems of overhead cranes in both theory and practice have attracted many researchers. Various kinds of crane control techniques have been applied from classical methods such as linear control [1], nonlinear control [2, 5, 6], optimal approach [7], adaptive algorithms [8, 9] to modern techniques such as fuzzy logic [3, 4, 10], neural network [11], command shaping [12], and so on.
The abovementioned researches deal with crane motion modeled as pendulum or multi-section pendulum systems. As a result, their dynamics are described as an ordinary differential equation or a system of ordinary differential equations. In practice, the crane rope exhibits a certain degree of flexibility; hence, the equation of motions of the gantry crane with flexible rope is represented by a set of partial differential and ordinary differential equations. In [13, 14, 15], the authors successfully design a controller that can stabilize the system with the rope flexibility. Flexible rope also is considered in [16, 17] where coupled longitudinal-transverse motion and 3D model are investigated.
This chapter accesses the modeling and control of overhead cranes according to the other research direction. We construct a distributed model of overhead cranes in which the mass and the flexibility of payload suspending cable are fully taken into account. We utilize the analytical mechanics including Hamilton principle for constructing such the mathematical model. With the received model, we analyze and design two nonlinear control algorithms based on two versions of Lyapunov stability: one is the so-called traditional Lyapunov function and the other is the so-called barrier Lyapunov. Dissimilar to the preceding study [18, 19] whereas the problem of actuated payload positioning system is considered, the proposed controllers track the trolley to destination precisely while keeping the payload swing small during the transport process and absolutely suppressed at the payload destination with control forces exerted at the trolley end of the system. The quality of control system is investigated by numerical simulation. Since the system dynamics is characterized by a distributed mass model, the finite difference method is applied to simulate the system responses in MATLAB® environment.
The chapter content is structured as follows. Section 2 constructs a distributed mass model of overhead cranes. Section 3 analyzes and designs two nonlinear controllers based on Lyapunov direct theory. The analysis of system stability is included. Section 4 numerically simulates the system responses and analyzes the received results. Finally, the remarks and conclusions are shown in Section 5.
2. Distributed mass modeling of overhead cranes
Let us constitute a mathematical model for overhead cranes fully considering the flexibility and mass of cable. In other words, payload handling cable with length L is considered as a distributed mass string with density
Before carrying system modeling, we assume that:
Moving masses at the trolley end are symmetrical in X and Y directions.
The gantry moving in XY plane and the rope length are unchanged.
Friction and external distributed forces are neglected.
Longitudinal deformation of the crane rope is negligible.
From this point onward, the argument (
With the differential derivation along the cable length L, the potential energy due to the elasticity of cable and gravity is determined by
where
With two force components to move trolley and bridge Fx and Fy, the total visual works of system are in the form of
Using the generalized form of Hamilton principle, one has the following equation:
in which the small variations of kinematic and potential energies, respectively, are described by
and the small derivation of virtual work is written as
First, one obtains
We define
and apply the following property:
with
We calculate the components of (10) using the expressions of partial integration as follows:
Inserting (11) and (12) into (10) leads to
Integrating the abovementioned equation in term of time side by side, one has
which yields
Next, let us calculate
with the below notations
and
Substituting (8), (13), (14), and (15) into (5), one obtains
which is simplified as
Consider the following boundaries at x = 0 and x = L:
which leads to
and
Submitting (18) into (19a) and (19b) in the interval [0, L] of z, one has
and
At boundary condition z = L, one obtains
and
At boundary condition z = 0, one has
and
In summary, the dynamic behavior of overhead crane governed a set of six nonlinear partial differential Eqs. (20), (21), (22), (23), (24), and (25), as follows:
The first and the second equations of the above system of equation represent dynamics of the gantry rope. Boundary conditions at load and trolley ends are given in the third, fourth, fifth, and sixth equations, respectively.
3. Lyapunov-based control design
Let us construct two nonlinear controllers using a traditional Lyapunov stability and its advanced version. In the first method, the control law is referred from the negative condition of a Lyapunov candidate
3.1. Conventional Lyapunov controller
The following theorem points out a nonlinear controller designed based on the second method of Lyapunov stability. The proposed control scheme tracks the outputs of a crane system approach to references asymptotically.
and
pushes all state outputs of dynamic model (20)–(25) to reference
where
With the notations that
one has
with
and
Differentiating Lyapunov function (28) with respect to time, one obtains
Let us calculate the components of Lyapunov derivative (29). We refer from (20) and (21) that
Using partial integration
and
one obtains the following components of (30) as follows:
and
Then,
and
The Lyapunov derivative (29) now becomes
Additionally, modification of (24) and (25) yields
Submitting (32) into (31) with a series of calculation, we obtain
Substituting the control law (26) and (27) into (33) leads the Lyapunov function to
With the negative definition of expression (34), we can conclude that the system is now exponential stability.
3.2. Barrier Lyapunov controller
We utilize an improved version of Lyapunov stability to design a control law for overhead cranes. The Lyapunov function is chosen so that its derivative is smaller than a positive constant. By this way, the Lyapunov candidate is selected similar to Eq. (28) but supplementing derivation of payload position
where
Applying the following inequality
or
with K being positive constant leads to
Inserting (37) into (36) yields
Inserting the following inequality
or
into (38), one obtains
To force the Lyapunov differentiation being negative, the control law with two components is structured as
and
which leads the Eq. (31) to
for every positive gains K
4. Simulation and results
Consider the case that only the trolley motion is activated, we numerically simulate the distributed system dynamics (20)–(25) driven by either conventional Lyapunov-based input or barrier Lyapunov-based law. The finite difference method is applied for programing the control system in MATLAB environment. The system parameters used in simulation are composed of
The simulation results are depicted in
Figures 3
–
6
. Trolley and payload approach to destination
5. Conclusions
The dynamic model of overhead crane with distributed mass and elasticity of handling cable is formulated using the extended Hamilton’s principle. Based on the model, we successfully analyzed and designed two nonlinear robust controllers using two versions of Lyapunov candidate functions. The first can steer the payload to the desired location, while the second can maintain payload fluctuation in a defined span. The proposed controllers well stabilize all system responses despite the large variation of cable length and payload weight. Enhancing for 3D motion with carrying rope length will be proposed in the future studies.
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