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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:
93D20Asymptotic stability of control systems
93D25Input-output approaches to stability of control systems
93C42Fuzzy control systems
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