Output tracking control of switched nonlinear singular system using neural networks

In this paper, we address the tracking problem for a class of switched nonlinear singular SISO/MIMO systems based on RBF neural network. Adaptive neural network switched controller is designed for the above problem under the case that singular matrix of all subsystems is same. The RBF neural network is used to approximate the unknown part of switched nonlinear singular 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. The adaptive neural network switched controller is designed to attenuate approximation errors of the RBF neural networks guarantee asymptotic stability of the output tracking error for the switched nonlinear singular system.