4.8 Article

Intermittent Event-Triggered Exponential Stabilization for State-Dependent Switched Fuzzy Neural Networks With Mixed Delays

Journal

IEEE TRANSACTIONS ON FUZZY SYSTEMS
Volume 30, Issue 8, Pages 3312-3321

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TFUZZ.2021.3112256

Keywords

Switches; Control systems; Neural networks; Delays; Fuzzy neural networks; Fuzzy control; Synchronization; Fuzzy logic; intermittent event-triggered control; neural networks; stabilization; state-dependent switched

Funding

  1. Qatar National Research Fund [NPRP13S-0116-200085]
  2. Open Research Fund of the Key Laboratory of Advanced Perception and Intelligent Control of High-end Equipment, Ministry of Education, Anhui Polytechnic University [GDSC202012]

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This article discusses and resolves the issue of intermittent event-triggered exponential stabilization for state-dependent switched fuzzy neural networks with mixed delays. An intermittent event-triggered control strategy is proposed to reduce the amount of samplings and save control costs. The theoretical analysis results are verified through a simulation example.
In this article, the issue of intermittent event-triggered exponential stabilization for state-dependent switched fuzzy neural networks with mixed delays is discussed and resolved. By combining event-triggered control with intermittent control, an intermittent event-triggered control strategy is proposed, which only focuses on events during control time. Consequently, compared with some existing event-triggered control strategies, it greatly reduces the amount of samplings and saves control costs. Based on the fuzzy intermittent event-triggered controller designed in this article, two event-triggering mechanisms are proposed to determine the trigger instants. In this context, some easily testified algebraic conditions are obtained for the exponential stabilization of the state-dependent switched fuzzy neural networks with mixed delays. In addition, a positive lower bound for the inter-event time is given. The results of theoretical analysis are verified through a simulation example.

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