Event-Triggered Stabilization for Takagi–Sugeno Fuzzy Complex-Valued Memristive Neural Networks With Mixed Time-Varying Delays
Xiaofan Li, Tingwen Huang, Jian‐an Fang
Abstract
This article is devoted to solving the event-triggered stabilization problem of a new type of Takagi–Sugeno fuzzy complex-valued memristive neural networks with mixed time-varying delays. By introducing an event-triggered scheme with static and dynamic event-triggered conditions, the fuzzy event-triggered controller is designed. After combining the inequality technique with the Lyapunov function approach, some easily verified sufficient conditions are established to ensure stabilization of the Takagi–Sugeno fuzzy complex-valued memristive neural networks with mixed time-varying delays under the proposed event-triggered scheme. In addition, since the inter-event time with the proposed event-triggered scheme is deduced to exist a nonzero positive lower bound, Zeno behavior is not going to happen. Finally, the effectiveness of results is verified by a numerical example.