Optimal Fuzzy Design Of Chua'S Circuit System

This paper addresses the robust controller design problem for a class of fuzzy-neural systems that are robust against both the plant parameter perturbations and controller gain variations. More specifically, the purpose is to synthesize a piecewise Static Output Feedback (SOF) controller guaranteeing the stability of the resulting closed-loop fuzzy-neural dynamic system. Based on piecewise quadratic Lyapunov functions and the relaxed method with Neural Network Differential Inclusion (NNDI), the intelligent approach can be stabilized by regulating appropriately the parameters of dither and this robust controller gains can be obtained by solving a set of Linear Matrix Inequalities (LMIs). The superiority of proposed method is verified through numerical examples. Because the design of efficient and high-performance control systems is of fundamental interest to engineers, systematic methodologies are to be used for the combined intelligent and active control system synthesis in many applications.