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Abstract and Applied Analysis
Volume 2014 (2014), Article ID 462468, 10 pages
http://dx.doi.org/10.1155/2014/462468
Research Article

Direct Adaptive Tracking Control for a Class of Pure-Feedback Stochastic Nonlinear Systems Based on Fuzzy-Approximation

1School of Mathematics and Physics, Bohai University, Jinzhou, Liaoning 121000, China
2Faculty of Engineering, Lakehead University, Orillia, Thunder Bay, ON, Canada P7B 5E1
3Faculty of Electronic and Information Engineering, Liaoning University of Science and Technology, Anshan, Liaoning 114051, China
4College of Information Science and Technology, Bohai University, Jinzhou, Liaoning 121000, China
5Department of Engineering, Faculty of Engineering and Science, University of Agder, 4898 Grimstad, Norway

Received 14 November 2013; Accepted 6 January 2014; Published 13 February 2014

Academic Editor: Xiaojie Su

Copyright © 2014 Huanqing Wang et al. 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.

Abstract

The problem of fuzzy-based direct adaptive tracking control is considered for a class of pure-feedback stochastic nonlinear systems. During the controller design, fuzzy logic systems are used to approximate the packaged unknown nonlinearities, and then a novel direct adaptive controller is constructed via backstepping technique. It is shown that the proposed controller guarantees that all the signals in the closed-loop system are bounded in probability and the tracking error eventually converges to a small neighborhood around the origin in the sense of mean quartic value. The main advantages lie in that the proposed controller structure is simpler and only one adaptive parameter needs to be updated online. Simulation results are used to illustrate the effectiveness of the proposed approach.