Intelligent Control of General Nonlinear Systems via Generalized T-S Fuzzy Models

Description

Intelligent control based on Takagi-Sugeno (T-S) fuzzy models has attracted great attention from control community, and a large volume of results have been published in recent years. These include results on T-S fuzzy system modeling and identification, universal function approximation, stability analysis, and controller synthesis. However, it has been shown most recently that the commonly used T-S fuzzy models can only be used to approximate affine nonlinear systems and thus most of those developed results on T-S fuzzy models can only be applicable to affine nonlinear systems. Then a natural question arises, that is, can one deal with control of general nonlinear systems via a T-S fuzzy model approach? In fact, many critical issues remain to be investigated when dealing with control of general rather than affine nonlinear systems via a T-S fuzzy model approach. For example, what kind of T-S fuzzy models can be used to approximate general nonlinear systems? How can controller synthesis of this kind of TS fuzzy models be effectively facilitated? Furthermore, suppose a general nonlinear system can be stabilized by an appropriately defined controller, does there exist a fuzzy controller to stabilize it? How can one design the fuzzy controller if it does exist? This project will investigate these issues and develop novel techniques or methodologies for intelligent control of general nonlinear systems via a T-S fuzzy model approach. The outcome of the project is expected to enrich the theoretical foundation of fuzzy model based intelligent control methodology and to provide more tools to control of general nonlinear systems which are expected to be widely utilized in practice.