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

来源：

IEEE TRANSACTIONS ON FUZZY SYSTEMS | 2021年 / 29卷 / 07期

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

页码：1853 / 1863

页数：11

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