Wavelet-based adaptive robust control for a class of MIMO uncertain nonlinear systems

2010 ◽  
Vol 21 (4) ◽  
pp. 747-762 ◽  
Author(s):  
Chiu-Hsiung Chen
Keyword(s):  
Robust Control ◽  
Nonlinear Systems ◽  
Adaptive Robust Control ◽  
Uncertain Nonlinear Systems

Adaptive Robust Control of a Class of Uncertain Nonlinear Systems Based on Backstepping

2013 ◽  
Vol 389 ◽  
pp. 441-447
Author(s):  
Hai Bo Zhao ◽  
Yun Guo Zhu
Keyword(s):  
Robust Control ◽  
Nonlinear Systems ◽  
Adaptive Controller ◽  
Adaptive Robust Control ◽  
Uncertain Nonlinear Systems ◽  
Globally Asymptotically Stable ◽  
Adaptive Law ◽  
Bounded Disturbances ◽  
Bounded Disturbance ◽  
Control Quantity

Aiming at the control of a class of bounded disturbance uncertain nonlinear systems,we applied robust control and backstepping control,introduced the concept of virtual control quantity,chose Lyapunov function through stepwise recursion,offered the adaptive law of parameters estimate,designed an adaptive controller with state feedback in the premise of unknown uncertain parameters in the systems, and analyzed its stability. Compared with the conventional PID control in simulation results, the designed controller has the better robustness of the system parameter uncertainty and bounded disturbances, and can ensure the entire closed-loop system is globally asymptotically stable, thus verifying the effectiveness of the proposed control strategy.

Wavelet Neural Network Based Adaptive Robust Control for a Class of MIMO Nonlinear Systems

2011 ◽  
Vol 383-390 ◽  
pp. 290-296
Author(s):  
Yong Hong Zhu ◽  
Wen Zhong Gao
Keyword(s):  
Neural Network ◽  
Robust Control ◽  
Nonlinear Systems ◽  
Wavelet Neural Network ◽  
Adaptive Robust Control ◽  
Loop Control ◽  
Control Approach ◽  
Mimo Nonlinear Systems ◽  
Output Tracking Control ◽  
Dynamic Inverse

Wavelet neural network based adaptive robust output tracking control approach is proposed for a class of MIMO nonlinear systems with unknown nonlinearities in this paper. A wavelet network is constructed as an alternative to a neural network to approximate unknown nonlinearities of the classes of systems. The proposed WNN adaptive law is used to compensate the dynamic inverse errors of the classes of systems. The robust control law is designed to attenuate the effects of approximate errors and external disturbances. It is proved that the controller proposed can guarantee that all the signals in the closed-loop control system are uniformly ultimately bounded (UUB) in the sense of Lyapunov. In the end, a simulation example is presented to illustrate the effectiveness and the applicability of the suggested method.

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