ROBUST ADAPTIVE TRACKING CONTROL FOR NONLINEAR SYSTEMS BASED ON SELF-ORGANIZING FUZZY CMAC NEURAL NETWORKS
基于自组织模糊CMAC网络的非线性系统鲁棒自适应跟踪控制

This paper presents a method of robust adaptive tracking control for nonlinear systems based on a self organizing fuzzy CMAC neural network. The on line learning while controlling neural network is used to adaptively regulate the error in the plant inversion which may be due to modeling uncertainties and disturbances in order to make the system outputs accurately track the outputs of the reference model. The updating rule of SOFCMAC weights is derived from Lyapunov stability theory. The stability of the designed system is proved. Simulation results demonstrate the effectiveness of the proposed method.