Adaptive Fuzzy/Neural Control and its Applications in Nonlinear Systems
Wei Jia · Computing Technology and Automation · 2005
In this paper,for a class of unknown continual nonlinear systems,an observer-based adaptive fuzzy/neural control algorithm which can satisfy the stability and boundedness of the systems is developed.The algorithm makes use of T-S(Takagi-Sugeno) fuzzy systems or radial-basis functions to construct the indirect adaptive controller,whose parameters can be adjusted on line according to the control law and the adaptive law in order to provide asymptotic tracking of a reference signal of the nonlinear plants.The Lyapunov-synthesis approach is utilized to insure the stability of the system.Simulation results of the inverted pendulum system are represented to show the feasibility of the algorithm in controlling nonlinear systems.