Design of sampled-data control for multiple-time delayed generalised neural networks based on delay-partitioning approach. Issue 13 (3rd October 2017)

• Record Type: Journal Article
• Authors: Ali, M. Syed; Gunasekaran, N.; Aruna, B.
• Is Part Of: International journal of systems science. Volume 48:Issue 13(2017)
• Page Start: 2794
• Page End: 2810
• Publication Date: 2017-10-03
• Subjects: Delay-partitioning approach -- generalised neural networks -- time-delays -- linear matrix inequalities (LMIs) -- Lyapunov method -- sampled-data control; System analysis -- Periodicals; 003.3
• DOI: 10.1080/00207721.2017.1344891
• Languages: English
• ISSNs: 0020-7721

Abstract

ABSTRACT: In this paper, we addressed the problem of stability analysis for a class of generalised mixed delayed neural networks by delay-partitioning approach. A novel integral inequality is developed by employing Wirtinger's integral inequality and Leibniz–Newton formula. By constructing an augmented Lyapunov–Krasovskii functional with triple and quadruple integral terms and using some standard integral inequality techniques, asymptotic stability criterion is obtained to the concerned neural networks. By converting the sampling period into a bounded time-varying delays, the error dynamics of the considered generalised neural networks are derived in terms of a dynamic system with sampling. Finally, numerical examples are given to show that the proposed method is less conservative than existing ones.