Abstract
The dynamic model of overhead crane is highly nonlinear and uncertain. In this paper, Takagi-Sugeno (T-S) fuzzy modeling and PSO-based robust linear quadratic regulator (LQR) are proposed for anti-swing and positioning control of the system. First, on the basis of sector nonlinear theory, the two T-S fuzzy models are established by using the virtual control variables and approximate method. Then, considering the uncertainty of the model, robust LQR controllers with parallel distributed compensation (PDC) structure are designed. The feedback gain matrices are obtained by transforming the stability and robustness of the system into linear matrix inequalities (LMIs) problem. In addition, particle swarm optimization (PSO) algorithm is used to overcome the blindness of LQR weight matrix selection in the design process. The proposed control methods are simple, feasible, and robust. Finally, the numeral simulations are carried out to prove the effectiveness of the methods.
Highlights
Overhead crane is a popular underactuated mechanical system, which is widely used to carry and lift goods indoors or outdoors
On the basis of sector nonlinear theory, the two T-S fuzzy models are established by using the virtual control variables and approximate method
In [36], a guaranteed cost fuzzy controller with input/state constraints is designed for overhead cranes, in which the traditional T-S fuzzy systems are replaced by fuzzy description systems
Summary
Overhead crane is a popular underactuated mechanical system, which is widely used to carry and lift goods indoors or outdoors. There are many methods for anti-swinging and positioning control of cranes. In [36], a guaranteed cost fuzzy controller with input/state constraints is designed for overhead cranes, in which the traditional T-S fuzzy systems are replaced by fuzzy description systems This method can eliminate the residual swing angle of the load, but the uncertainty of the system model is not considered when designing the controller. In order to solve the nonlinear and uncertain problems of dynamics model, a novel anti-swing and positioning control method for overhead crane is presented in this paper. (2) Aiming at the anti-swing and positioning control of overhead crane, a robust LQR control method is presented on the basis of T-S fuzzy models considering uncertainty.
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