state estimation of generalised neural networks with interval time-varying delays

R. Saravanakumar, M. Syed Ali, Jinde Cao and He Huang

International Journal of Systems Science, 2016, vol. 47, issue 16, 3888-3899

Abstract: This paper focuses on studying the H∞ state estimation of generalised neural networks with interval time-varying delays. The integral terms in the time derivative of the Lyapunov–Krasovskii functional are handled by the Jensen’s inequality, reciprocally convex combination approach and a new Wirtinger-based double integral inequality. A delay-dependent criterion is derived under which the estimation error system is globally asymptotically stable with H∞ performance. The proposed conditions are represented by linear matrix inequalities. Optimal H∞ norm bounds are obtained easily by solving convex problems in terms of linear matrix inequalities. The advantage of employing the proposed inequalities is illustrated by numerical examples.

Date: 2016
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DOI: 10.1080/00207721.2015.1135359

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