Nonlinear System Modeling And Control Based On T-S Fuzzy Model With Growing And Pruning Rules

Due to the present inferior theories of nonlinear system, it is always difficult to model and control a nonlinear system. Among diverse approaches for that, fuzzy system, with its linguistic description and nonlinear character, can achieve and handle qualitative information, therefore a fuzzy model for nonlinear system can reflect its nonlinear character well. Furthermore, T-S fuzzy system combining the fuzzification capability and brief expression as a linear model fits the nonlinear modeling and controller design based on it. Thus it is widely applied in the nonlinear system control problem, whereas its own theory is being developed and dozens of structural and parameter identification methodologies come out.However, those methodologies have not achieved a profound research for number of fuzzy rules, which makes us confront with the different number of rules found by different methods and lack of adaptability during modeling and control. Hence, this thesis reveals...