Adaptive fuzzy approach for a class of uncertain nonlinear systems in strict-feedback form.
Adaptive fuzzy control is proposed for a class of affine nonlinear systems in strict-feedback form with unknown nonlinearities. The unknown nonlinearities include two types of nonlinear functions: one satisfies the "triangularity condition" and can be directly approximated by fuzzy logic system, while the other is assumed to be partially known and consists of parametric uncertainties. Takagi-Sugeno type fuzzy approximators are used to approximate unknown system nonlinearities and the design procedure is a combination of adaptive backstepping and generalized small gain design techniques. It is proved that the proposed adaptive control scheme can guarantee the uniformly ultimately bounded (UBB) stability of the closed-loop systems. Simulation studies are shown to illustrate the effectiveness of the proposed approach.
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The Hong Kong Polytechnic University, Department of Electrical Engineering, Hung Hom, Kowloon, Hong Kong. eehfho@polyu.edu.hk
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D000465:Algorithms; D003198:Computer Simulation; D005246:Feedback; D017143:Fuzzy Logic; D015233:Models, Statistical; D017711:Nonlinear Dynamics