Research On Sliding Mode Control Theory Of Nonlinear System

Variable structure control, as a independent research branch, had been promoted and applied in the practical program, such as motor control and power systems, robot control, aircraft control, satellite attitude control etc.Study of nonlinear system control problem is the focus in the research of sliding mode control in domestic and abroad recently, thus the study of sliding mode control problem of nonlinear systems has an important value in theory and practice.In this paper, we had learned the knowledge of nonlinear system sliding mode control. Since the features of sliding mode control, we concerned to combine it with neural network and fuzzy control. The contributions of this paper are as follows:First, according to the learning ability and powerful mapping ability for nonlinear system of neural network, we obtained the adaptive sliding mode control based neural network. Design the adaptive sliding mode controller based on neural network for the complex nonlinear system with uncertainty and time-delay. Stability analysis of the system is given by using Lyapunov function. Simulation results demonstrate the sliding mode controller based on neural network can reduce position tracking error and chattering of the system effectively compared to general sliding mode controller.Second, fuzzy control is particularly applicable to the complex nonlinear system which is hard to establish mathematical model. Combine fuzzy control with advantages of sliding mode control, using fuzzy control soften the control signal then it can reduce or avoid the chattering phenomenon of general sliding mode control. Design adaptive sliding mode controller based on fuzzy control theory for nonlinear system and it is proved that the controller can stabilize the system. Simulation results demonstrate the sliding mode controller based on fuzzy control theory can reduce position tracking error and chattering of the system effectively compared to general sliding mode controller.Third, the intersection and integration of fuzzy control and neural network gives rise to fuzzy neural network (FNN). Fuzzy neural network control combines both advantages of neural network and fuzzy control. Controller based on fuzzy neural network theory can not only eliminated chattering completely but also insure system that is robust. Controller designed through the program proposed in this paper can reduce chattering of the system effectively and make system immunity.