Intelligent fuzzy control with imperfect premise matching concept for complex nonlinear multiplicative noised systems

摘要

This paper provides the criterion for discussing stability analysis and synthesis of a class of complex nonlinear systems represented by Takagi-Sugeno fuzzy models with multiplicative noise. In the consequent part of the T-S fuzzy models, the Ito's stochastic differential equations are introduced to represent the linear subsystems with multiplicative noise. Under the concept of imperfect premise matching, a novel fuzzy controller is designed without limitation of sharing the same membership function of fuzzy models. In other words, the imperfect premise matching technique provides a more general approach in designing fuzzy controllers. The advantage of the proposed fuzzy controller design method is that it can be enhanced more flexibility and robustness than well-known parallel distributed compensation based fuzzy control approach. At last, two numerical examples are given to illustrate the usefulness and effectiveness of proposed fuzzy controller design method.