Mathematical Problems in Engineering
Volume 2011 (2011), Article ID 604391, 25 pages
Research Article

Robust Adaptive Control for Nonlinear Uncertain Systems Using Type-2 Fuzzy Neural Network System

Department of Electrical Engineering, Yuan Ze University, Chung-li, Taoyuan 320, Taiwan

Received 15 December 2010; Revised 19 March 2011; Accepted 6 April 2011

Academic Editor: Wei-Chiang Hong

Copyright © 2011 Ching-Hung Lee and Yu-Ching Lin. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper proposes a novel intelligent control scheme using type-2 fuzzy neural network (type-2 FNN) system. The control scheme is developed using a type-2 FNN controller and an adaptive compensator. The type-2 FNN combines the type-2 fuzzy logic system (FLS), neural network, and its learning algorithm using the optimal learning algorithm. The properties of type-1 FNN system parallel computation scheme and parameter convergence are easily extended to type-2 FNN systems. In addition, a robust adaptive control scheme which combines the adaptive type-2 FNN controller and compensated controller is proposed for nonlinear uncertain systems. Simulation results are presented to illustrate the effectiveness of our approach.