Stability of Stochastic Coupled Networks with Time-Varying Coupling Under Intermittent Event-Triggered Control
This paper studies the exponential stability in the mean square of the stochastic complex networks with time-varying coupling under an intermittent dynamic event-triggered control. A dynamic term and an exponential function are introduced into the event-triggered mechanism to reduce the number of control updates. Simultaneously, the minimum inter-execution time for every sample path solution of the stochastic complex networks, independent mathematical expectation, is obtained. Unlike previous research, the event-triggered mechanism under the stochastic version is more reasonable due to the absence of mathematical expectations in the event-triggered function. Furthermore, using the average control rate for intermittent strategy and the Lyapunov method, sufficient conditions for exponential stability in the mean square under intermittent dynamic event-triggered control are derived. Finally, an example with numerical simulations is provided to validate the feasibility of the theoretical results.
Authors
- Bing Jiang (ORCID: https://orcid.org/0000-0001-5389-3293)
- Yongbao Wu (ORCID: https://orcid.org/0000-0001-7670-7393)
Institutions
- Hangzhou Wanxiang Polytechnic (CN)
- Zhejiang University (CN)
- Southeast University (CN)
Publication Details
- Journal
- Actuators
- Published
- 2024-11-24
- DOI
- https://doi.org/10.3390/act13120475
- Citations
- 1
- Primary Topic
- Neural Networks Stability and Synchronization
- Type
- article
- Field-Weighted Citation Impact
- 0.35