Study On Stability Control Of Nonlinear Systems Based On T-S Fuzzy Model

As we all know that nonlinear systems exist in the world extensively, so it is important to investigate the stability analysis and control of nonlinear systems. As for nonlinear systems, it is difficult to get the accurate mathematic model. Even we can build mathematic model for those systems, it may be too complicated to design a controller with conventional means. It is the artificial intelligent control based on knowledge that takes bright future for the above problems. The study of this paper is based on the T-S fuzzy model of nonlinear system.By using a guaranteed cost control(GCC) approach, the problem of Takagi-Sugeno(T-S) fuzzy fault tolerant control design via linear Matrix Inequality(LMI) is presented. The sufficient condition for a class of nonlinear systems with actuator fault is obtained. This method guarantees the stability of this system. The problem of designing a fuzzy generalized controller is studied for a class of nonlinear continuous time-delay systems with uncertainty. The sufficient conditions are got for the existence of robust fuzzy controllers. Simulation shows the effectiveness of this method. The problem of designing a delay-dependent fuzzy guaranteed cost controller is studied. The sufficient conditions, equaling to three kinds of linear matrix inequalities, are obtained for the existence of delay-dependent guaranteed cost fuzzy controllers. Furthermore, a convex optimization problem with LMI constraints is formulated to design the optimal guaranteed cost controller.As for a class of nonlinear neutral delay systems with norm-bounded uncertainty, the problem of designing a fuzzy guaranteed cost controller is studied. Through selecting the special Lyapunov function and transforming, the sufficient conditions for the stable system are got. Furthermore, a convex optimization problem with LMI constraints is formulated to design the optimal guaranteed cost controller. The problem of designing fuzzy controller is studied. Based on genetic algorithm, a class of nonlinear chaotic system is investigated. We applied the genetic algorithm to optimize the parameters of membership function of fuzzy controller, which integrates the global searching and high precision of genetic algorithm and the celerity of the fuzzy controller. On the other hand, it is suggested for the problem of chaos anti-control. According to the definition of the anti-control of chaotic systems, tracking control is introduced subtly. For a class of nonlinear chaotic systems based on T-S fuzzy model, the chaos anti-controlling of continuous time stable linear system is successfully realized. The method suggested need not estimate the Lyapunov exponent of the chaotic system, and can dramatically reduce the computation. Furthermore, this method lowers the conservation, which widens this theory's application.