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

Institutions

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
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Stability of Stochastic Coupled Networks with Time-Varying Coupling Under Intermittent Event-Triggered Control

Bing Jiang, Yongbao Wu
1 citations
Actuators
Neural Networks Stability and Synchronization
0.35
article

Stability of Stochastic Coupled Networks with Time-Varying Coupling Under Intermittent Event-Triggered Control

Bing Jiang, Yongbao Wu
article en
1 citations

Abstract

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.

ActuatorsVol. 13(12)
Hangzhou Wanxiang Polytechnic (CN), Zhejiang University (CN), Southeast University (CN)
Openalex Percentile: Top 36%
Neural Networks Stability and Synchronization
0.35
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Stability of Stochastic Coupled Networks with Time-Varying Coupling Under Intermittent Event-Triggered Control — Bing Jiang, Yongbao Wu · Actuators (2024) | TGRS Research Map | TGRS