作者: Yanjun Zhang , Gang Tao , Mou Chen
关键词: Fuzzy control system 、 Nonlinear control 、 Adaptive control 、 Fuzzy logic 、 Linearization 、 Adaptive neuro fuzzy inference system 、 Mathematics 、 Mathematical optimization 、 Control theory 、 Feedback linearization 、 Adaptive system
摘要: This paper develops a new adaptive feedback linearization based control scheme for T-S fuzzy systems in general non-canonical forms, which provides an effective method to form nonlinear with large parameter uncertainties. Unlike commonly studied canonical whose approximation models have explicit relative degree structures can be directly used derive parametrized controllers adaptation, usually do not degrees as their system are also forms. In order achieve output tracking, the dynamics of still needs parametrized. extends technique, tracking systems, and guarantees closed-loop stability asymptotic models. An illustrative example is presented simulation results demonstrate design procedure, verify effectiveness such method.