Sampled-data-based dynamic event-triggered formation control for nonlinear multi-agent systems
Xiaofeng Chai, Qing Wang, Qi Diao, Yao Yu, Changyin Sun · Transactions of the Institute of Measurement and Control · 2022
This paper studies the distributed formation control of multi-agent systems with nonlinear dynamics. In view of practical digital microprocessor and limited network resources, the sampled-data-based dynamic event-triggered control strategy is developed. First, each agent synchronously samples its states and monitors the event-triggered function periodically. Each agent broadcasts its states to neighbors only when the function is triggered which can greatly reduce communication times. Meanwhile, the Zeno behavior is excluded due to periodic sampling. Moreover, the dynamic parameter in event-triggered function updates in accordance with a dynamic rule which helps achieve a trade-off between communication frequency and formation performance. The formation problem is transformed into the stability analysis of a time-delay system. Finally, numerical simulations are shown to illustrate the effectiveness of the proposed strategy.