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Some new results on stability of Takagi-Sugeno fuzzy Hopfield neural networks. (English) Zbl 1234.93088

Summary: We propose some new results on stability properties of Takagi–Sugeno fuzzy Hopfield neural networks with time-delay. Based on Lyapunov stability theory, a new learning law is derived to guarantee passivity and asymptotic stability of Takagi–Sugeno fuzzy Hopfield neural networks. Furthermore, a new condition for Input-to-State Stability (ISS) is established. Illustrative examples are given to demonstrate the effectiveness of the proposed results.

MSC:

93D20 Asymptotic stability in control theory
93D25 Input-output approaches in control theory
93C42 Fuzzy control/observation systems

Software:

LMI toolbox
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References:

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