Abstract. This paper studies the problem of guaranteed cost control for a class of uncertain switched recurrent delayed neural networks. The time delay is a continuous function belonging to a given interval, but not necessary to be differentiable. A cost function is considered as a nonlinear performance measure for the closed-loop system. The stabilizing controllers to be designed must satisfy some stability constraints on the closed-loop poles. By constructing a set of augmented Lyapunov-Krasovskii functional combined with Newton-Leibniz formula, a guaranteed cost controller is designed via memoryless state feedback control and new sufficient conditions for the existence of the guaranteed cost state-feedback for the system are given in terms of linear matrix inequalities (LMIs). A numerical examples are given to illustrate the effectiveness of the obtained result.

Received: February 6, 2014

AMS Subject Classification: 15A09, 52A10, 74M05, 93D05, 94C10, 92B20

Key Words and Phrases: uncertain switched recurrent neural networks, guaranteed cost control, stabilization, interval time-varying delays, Lyapunov function, linear matrix inequalities

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DOI: 10.12732/ijpam.v95i4.4 How to cite this paper?

Source: International Journal of Pure and Applied Mathematics
ISSN printed version: 1311-8080
ISSN on-line version: 1314-3395
Year: 2014
Volume: 95
Issue: 4
Pages: 523 - 533

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This work is licensed under the Creative Commons Attribution International License (CC BY).

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