Robust exponential stability and H ∞  control for switched neutral‐type neural networks. (28th August 2012)

• Record Type: Journal Article
• Authors: Mathiyalagan, K.; Sakthivel, R.; Marshal Anthoni, S.; Xu, Xin; Wang, Cong; Lewis, Frank L.
• Is Part Of: International journal of adaptive control and signal processing. Volume 28:Number 3/5(2014)
• Page Start: 429
• Page End: 443
• Publication Date: 2012-08-28
• Subjects: Adaptive control systems -- Periodicals; Adaptive signal processing -- Periodicals; 629.836
• DOI: 10.1002/acs.2332
• Languages: English
• ISSNs: 0890-6327

Abstract

<abstract abstract-type="main" id="acs2332-abs-0001"> <title>SUMMARY</title> <p id="acs2332-para-0001">In this paper, we consider the problem of robust exponential stability for a class of uncertain switched delayed neutral‐type neural networks with an <italic>H</italic>_∞ performance level <italic>γ</italic> &gt; 0. Further, the result is extended to design an <italic>H</italic>_∞ control law to ensure the robust exponential stabilization of the closed‐loop neural networks about its equilibrium point with the guaranteed <italic>H</italic>_∞ performance level <italic>γ</italic>, for all norm bounded parameter uncertainties. On the basis of a new set of Lyapunov–Krasovskii functional, linear matrix inequality technique, and average dwell time approach, a set of novel sufficient conditions is derived for the existence of <italic>H</italic>_∞ performance and as well as existence of <italic>H</italic>_∞ control problem. The obtained results are derived in the form of convex optimization problems, which can be solved easily by the standard Matlab control toolbox. Numerical examples with simulation results are provided to illustrate the effectiveness of the proposed method. Copyright © 2012 John Wiley &amp; Sons, Ltd.</p> </abstract>