Mean-square consensus of a semi-Markov jump multi-agent system based on event-triggered stochastic sampling

This paper focuses on achieving leader-follower mean square consensus in semi-Markov jump multi-agent systems. To effectively reduce communication costs and control updates, we propose an event-triggered protocol based on stochastic sampling. The stochastic sampling interval randomly switches between finite given values, while the event-triggered function depends on the stochastic sampled data from neighboring agents. Using the event-triggered strategy, we present sufficient conditions to ensure mean square consensus. Finally, we provide a numerical example demonstrating the effectiveness of the theoretical results.

Automated summary

This paper focuses on achieving leader-follower mean square consensus in semi-Markov jump multi-agent systems. To reduce communication costs and control updates effectively, an event-triggered protocol based on stochastic sampling is proposed. The stochastic sampling interval randomly switches between finite given values, while the event-triggered function depends on the stochastic sampled data from neighboring agents. Sufficient conditions to ensure mean square consensus are presented using the event-triggered strategy, and a numerical example is provided to demonstrate the effectiveness of the theoretical results.