Robust Control Of Uncertain Nonlinear T-S Fuzzy Systems

With development of science, technology and productivity, the controlled plants are becoming more and more complex. For lack of accurate mathematical model, and there exit various nonlinear sections, uncertainties. As we know T-S fuzzy model can approximate nonlinear systems significantly, and it is easy for us to analyze. The stability analysis and systematic design of fuzzy systems have been the most important issues for fuzzy control systems due to the special description and the natural nonlinearity of fuzzy systems. After reviewing the recent results on fuzzy control theory, this paper studies the methods to analyze stability and design controller for the T-S fuzzy systems. The main contents are as follows:1. Based on Lyapunov stability theory, this paper studies the stability analysis and systematic design of T-S fuzzy systems with uncertainties, and the proposed methods are transformed to equivalent LMI convex optimization problem, which can be numerically solved.2. The problem of uncertainties T-S fuzzy system is studied. the fuzzy controller and the robust stability in continues state are proposed. Meanwhile, this paper proposed the state feedback controller and the stability criteria in discrete state. With linear matrix inequality, analysis the stability condition for both states. The numerical can demonstrate the efficiency of the more relax approaches.3. For a class uncertain nonlinear system, T-S fuzzy model construction is first proposed. Then, the output feedback controller and observer are designed for continue and discrete T-S fuzzy systems. And then, proposed the state feedback controller robust stability of uncertainties T-S fuzzy system in LMI. The example and numerical can demonstrate the efficiency of the more relax approaches.