H-infinity control for switched nonlinear systems based on RBF neural networks

Sub-controller and switching strategy based on RBF neural network are presented for a class of switched nonlinear systems in this paper. Subcontroller consists of equivalent controller and H-infinity controller. RBF neural network is used to approximate the unknown part of switched nonlinear systems, and the approximation errors of the RBF neural networks are introduced to the adaptive law in order to improve the performance of the whole systems. Sub-controller and switching strategy are designed to guarantee asymptotic stability of the output tracking error and to attenuate the effect of the external disturbance and approximation errors to a given level.