Title :
Adaptive Neuro-Fuzzy Control of Non-Affine Nonlinear Systems
Author :
Jia, Li ; Ge, Shuzhi Sam ; Chiu, Min-Sen
Author_Institution :
Dept. of Chem. & Biomolecular Eng., Nat. Univ. of Singapore
Abstract :
In this paper, an adaptive neuro-fuzzy controller is investigated for a class of non-affine nonlinear systems. Firstly, rigorous description and quantification of the approximation error of the neuro-fuzzy controller are discussed. Then a novel updating algorithm to adapt the weights, centers, and widths of the neuro-fuzzy controller is presented based on Lyapunov stability theory. It is shown that the proposed design method is able to guarantee the stability of the closed-loop system and the convergence of the tracking error. Finally, simulation results illustrate the effectiveness of the proposed adaptive neuro-fuzzy control scheme
Keywords :
Lyapunov methods; adaptive control; closed loop systems; control system synthesis; fuzzy control; neurocontrollers; nonlinear control systems; stability; Lyapunov stability theory; adaptive neuro-fuzzy control; closed-loop system; nonaffine nonlinear systems; Adaptive control; Approximation error; Control systems; Convergence; Design methodology; Lyapunov method; Nonlinear control systems; Nonlinear systems; Programmable control; Stability;
Conference_Titel :
Intelligent Control, 2005. Proceedings of the 2005 IEEE International Symposium on, Mediterrean Conference on Control and Automation
Conference_Location :
Limassol
Print_ISBN :
0-7803-8936-0
DOI :
10.1109/.2005.1467029
