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Delay-dependent exponential stability analysis of fuzzy delayed Hopfield neural networks: A fuzzy Lyapunov-Krasovskii functional approach

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2 Author(s)
Li Sheng ; Sch. of Commun. & Control Eng., Jiangnan Univ., Wuxi, China ; Huizhong Yang

This paper investigates the delay-dependent exponential stability problem of Takagi-Sugeno (TS) fuzzy Hopfield neural networks (HNNs) with time-varying delay. Based on a fuzzy Lyapunov-Krasovskii functional (LKF), some delay-dependent stability criteria guaranteeing the exponential stability of the fuzzy HNNs are devised by taking the relationship between the terms in the Leibniz-Newton formula into account. Since free weighting matrices are used to express this relationship and the appropriate ones are selected by means of linear matrix inequalities (LMIs), the criteria are less conservative than existing ones reported in the literature for delayed fuzzy neural networks. A simulation example is provided to illustrate the effectiveness of the developed method.

Published in:

American Control Conference, 2009. ACC '09.

Date of Conference:

10-12 June 2009