BMI-BASED STABILITY AND PERFORMANCE DESIGN FOR FUZZY CONTROL SYSTEMS

This paper presents the stability and performance design of fuzzy-model-based control systems subject to parameter uncertainties. A nonlinear controller with a favorable characteristic to relax the stability conditions is proposed to drive the system states of the nonlinear plant to follow those of a stable reference model. Stability and performance conditions in terms of bilinear matrix inequalities are derived based on a Lyapunov-based approach. A genetic-based convex programming technique process is developed to solve the solution to the bilinear matrix inequalities. An application example is given to show the merits of the proposed approach.