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Robust exponential stability and H ∞ control for switched neutral‐type neural networks
Author(s) -
Mathiyalagan K.,
Sakthivel R.,
Marshal Anthoni S.
Publication year - 2012
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/acs.2332
Subject(s) - exponential stability , control theory (sociology) , artificial neural network , convex combination , mathematics , convex optimization , equilibrium point , bounded function , norm (philosophy) , dwell time , matlab , mathematical optimization , linear matrix inequality , robust control , computer science , regular polygon , control (management) , control system , nonlinear system , law , engineering , artificial intelligence , mathematical analysis , differential equation , electrical engineering , operating system , medicine , clinical psychology , geometry , quantum mechanics , political science , physics
SUMMARY In this paper, we consider the problem of robust exponential stability for a class of uncertain switched delayed neutral‐type neural networks with an H ∞ performance level γ > 0. Further, the result is extended to design an H ∞ control law to ensure the robust exponential stabilization of the closed‐loop neural networks about its equilibrium point with the guaranteed H ∞ performance level γ , 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 H ∞ performance and as well as existence of H ∞ 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 & Sons, Ltd.