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Research Papers

Neural Adaptive Sliding Mode Control for a Class of Nonlinear Neutral Delay Systems

[+] Author and Article Information
Yugang Niu, Xingyu Wang

School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, PRC

James Lam

Department of Mechanical Engineering, University of Hong Kong, Pokfulam Road, Hong Kong

Daniel W. C. Ho

Department of Mathematics, City University of Hong Kong, Tat Chee Avenue, Hong Kong

J. Dyn. Sys., Meas., Control 130(6), 061011 (Oct 10, 2008) (7 pages) doi:10.1115/1.2977462 History: Received July 07, 2005; Revised May 20, 2008; Published October 10, 2008

This paper is concerned with the problem of sliding mode control (SMC) for a class of neutral delay systems with unknown nonlinear uncertainties that may not satisfy the norm-bounded condition. A SMC scheme based on neural-network approximation is proposed for the uncertain neutral delay system. By means of linear matrix inequality (LMI) approach, a sufficient condition is given such that the resultant closed-loop system is guaranteed to be stable, and the states asymptotically converge to zero. When the LMI is feasible, the designs of both the sliding surface and the sliding mode control law can be easily obtained via convex optimization. It is shown that the state trajectories are driven toward the specified sliding surface that depends on the current states as well as the delayed states. Finally, a simulation result is given to illustrate the effectiveness of the proposed method.

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Copyright © 2008 by American Society of Mechanical Engineers
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Figures

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Figure 1

Trajectories of state variable x(t)

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Figure 2

Trajectories of sliding variable s(t)

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Figure 3

Control signal u(t)

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