NDLI: Adaptive Control for a Class of Nonaffine Systems Based on Fuzzy-Neural Approach

Content Provider	IEEE Xplore Digital Library
Author	Jin, Y.Q. Wu, J.H. Gu, W.J.
Copyright Year	2006
Description	Author affiliation: Dept. of Control Eng., Naval Aeronaut. Eng. Inst., YanTai (Jin, Y.Q.; Wu, J.H.; Gu, W.J.)
Abstract	An adaptive control design method is proposed for a class of uncertain single-input single-output (SISO) nonaffine system based on fuzzy-neural approach. To the authors' knowledge, this control problem is firstly considered in this paper. It is considered difficult to be dealt with in the control literature, mainly because that the virtual controls and the final control law of uncertain nonaffine system are not easy to resolve. To overcome this difficulty, the fuzzy-neural approximator cancels the unknown part of the inverse functions adaptively. Then, inverse design, backstepping design, and feedback linearization techniques are incorporated to deal with this problem. It is proved that the whole closed-loop system is stable in the sense of Lyapunov. The control performance is guaranteed by suitably choosing the design parameters. Simulation study was included to demonstrate the effectiveness of the proposed method
Starting Page	519
Ending Page	523
File Size	627312
Page Count	5
File Format	PDF
ISBN	7302139229
DOI	10.1109/CESA.2006.4281708
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-10-04
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	IMACS
Subject Keyword	Backstepping Nonlinear control systems Control systems adaptive control Nonaffine system Adaptive control Neural networks Linear feedback control systems Linearization techniques fuzzy-neural approximator Systems engineering and theory backstepping Nonlinear systems Neurofeedback
Content Type	Text
Resource Type	Article

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