Title :
CMAC NN-based adaptive control of non-affine nonlinear systems
Author :
Xiaojun, Guo ; Yanli, Han ; Hu Yunan ; Youan, Zhang
Author_Institution :
Dept. of Autom. Control. Eng., Naval Aeronaut. Eng. Acad., China
Abstract :
Based on the implicit theorem and variable structure control (VSC), an adaptive control method is proposed for a class of non-affine nonlinear systems using CMAC neural networks (NN). The proposed controller ensures that the output of the system tracks a given bounded reference signal and that the output tracking error converges to the origin. The neural network weight learning laws are determined by Lyapunov stability theory and the stability of the closed loop system is guaranteed. The simulation results have shown the effectiveness of the proposed method
Keywords :
Lyapunov methods; adaptive control; cerebellar model arithmetic computers; closed loop systems; control system synthesis; neurocontrollers; nonlinear control systems; stability; variable structure systems; CMAC NN-based adaptive control; Lyapunov stability theory; bounded reference signal; neural network weight learning laws; nonaffine nonlinear system; output tracking error; variable structure control; Adaptive control; Aerospace engineering; Automatic control; Closed loop systems; Control systems; Error correction; Neural networks; Nonlinear control systems; Nonlinear systems; Trajectory;
Conference_Titel :
Intelligent Control and Automation, 2000. Proceedings of the 3rd World Congress on
Conference_Location :
Hefei
Print_ISBN :
0-7803-5995-X
DOI :
10.1109/WCICA.2000.863137
