Event-Triggered Stabilization for Takagi-Sugeno Fuzzy Complex-Valued Memristive Neural Networks With Mixed Time-Varying Delays

被引:35
作者
Li, Xiaofan [1 ,2 ]
Huang, Tingwen [3 ]
Fang, Jian-An [4 ]
机构
[1] Yancheng Inst Technol, Sch Elect Engn, Yancheng 224051, Peoples R China
[2] Anhui Polytech Univ, Minist Educ, Key Lab Adv Percept & Intelligent Control Highend, Wuhu 241000, Peoples R China
[3] Texas A&M Univ Qatar, Sci Program, Doha 5825, Qatar
[4] Donghua Univ, Coll Informat Sci & Technol, Shanghai 201620, Peoples R China
关键词
Neural networks; Takagi-Sugeno model; Delays; Delay effects; Stability analysis; Memristors; Time-varying systems; Complex-valued memristive neural networks; event-triggered scheme; stabilization; Takagi-Sugeno fuzzy logic; Zeno behavior; EXPONENTIAL STABILIZATION; MULTIAGENT SYSTEMS; STABILITY ANALYSIS; ROBUST STABILITY; SYNCHRONIZATION; CONSENSUS;
D O I
10.1109/TFUZZ.2020.2986713
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:1853 / 1863
页数:11
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