Intelligent Fuzzy Control with State-Derivative Feedback for Takagi-Sugeno Fuzzy Stochastic Singular Systems

Abstract

This document deals with the problem of passive fuzzy controller design with the state-derivative feedback approach for the nonlinear stochastic singular systems. Recently, the singular systems have a greater focus on literature because they can keep more physical system characteristics than conventional systems. At first, the Takagi-Sugeno fuzzy stochastic singular models are used to represent the nonlinear stochastic singular systems. Then, the state-derivative feedback approach and parallel distributed compensation method are employed to design the passive fuzzy controllers. In the design process, the Lyapunov stability conditions are developed subject to multiple performance constraints, including the passivity constraint and decay rate constraint. According to these Lyapunov stability conditions, the proposed fuzzy control problem can be effectively shifted into the linear matrix inequality problem that can be solved by using the convex optimal programming algorithm. At last, two examples are provided to verify the applicability and effectivity of the proposed passive fuzzy controller design approach.