Title :
Adaptive Control of a Class of Nonaffine Systems
Author :
Zibin, Xu ; Jianqing, Min
Author_Institution :
Modern Educ. Technol. Center, Zhejiang Shuren Univ., Hangzhou
Abstract :
An adaptive backstepping neural controller design is presented for a class of nonaffine nonlinear system with mismatched uncertainties. By applying backstepping design strategy and online approaching uncertainties with fully tuned radial basis function (RBF) neural networks (NNs), the adaptive tuning rules are derived from the Lyapunov stability theory. A nonlinear tracking differentiator is introduced to deal with the problem of extremely expanded operation quantity of backstepping method. The developed control scheme guarantees that all the signals of the closed-loop system are uniform ultimate boundedness. Simulation results are provided to show the good tracking performance and effectiveness of the proposed approach.
Keywords :
Lyapunov methods; adaptive control; closed loop systems; control system synthesis; neurocontrollers; nonlinear control systems; radial basis function networks; stability; time-varying systems; Lyapunov stability theory; adaptive backstepping neural controller design; adaptive tuning rules; closed-loop system; nonaffine nonlinear system; nonlinear tracking differentiator; radial basis function neural networks; Adaptive control; Adaptive systems; Backstepping; Control systems; Lyapunov method; Neural networks; Nonlinear control systems; Nonlinear systems; Programmable control; Uncertainty; adaptive control; backstepping; fully tuned RBF NNs; nonaffine systems;
Conference_Titel :
Knowledge Acquisition and Modeling Workshop, 2008. KAM Workshop 2008. IEEE International Symposium on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-3530-2
Electronic_ISBN :
978-1-4244-3531-9
DOI :
10.1109/KAMW.2008.4810425
