Title :
Switching adaptive control of a class of non-affine nonlinear systems
Author :
Liu Xiangbin ; Hou Zhongsheng ; Jin Shangtai
Author_Institution :
Adv. Control Syst. Lab., Beijing Jiaotong Univ., Beijing, China
Abstract :
In this paper, a performance-oriented switching adaptive control based on adaptive neural networks control and model-free adaptive control is proposed for a class of non-affine discrete time nonlinear systems. The method is composed of adaptive neural networks control, model-free adaptive control and a switching mechanism. The adaptive neural networks control ensures the transit performance and the model-free adaptive control is used to improve the final tracking performance. Switching scheme orchestrating between the two adaptive control algorithms can guarantee both the stability of controlled system and the control performance simultaneously. Stability and convergence analysis are given for the closed-loop system as well. Finally, simulation examples is presented to illustrate the effectiveness of the presented methods.
Keywords :
adaptive control; closed loop systems; convergence; discrete time systems; neurocontrollers; nonlinear control systems; stability; adaptive neural networks control; closed-loop system; control performance; convergence analysis; model-free adaptive control; nonaffine discrete time nonlinear systems; performance-oriented switching adaptive control; stability; switching mechanism; transit performance; Adaptation models; Adaptive control; Neural networks; Nonlinear systems; Switches; adaptive neural networks control; model-free adaptive control; non-affine nonlinear system; switching control;
Conference_Titel :
Control Conference (CCC), 2013 32nd Chinese