Sliding control for a class of MIMO uncertain nonlinear system based on neural networks

This paper describes a neural network based adaptive sliding control scheme to a class of MIMO (multi-input and multi-output) uncertain nonlinear system. The control scheme is made up of two parts. The first part is the design of an equivalent controller for the system which combines the approximation method of neural network, and the other part is the design of a sliding mode controller to diminish the track error and improve the robustness of the control system. The neural networks are used to approximate the nonlinear functions of uncertainty and the approximation errors are introduced to the adaptive law in order to improve the quality of this system. Finally, the simulation results show the effectiveness of the control scheme.