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A novel self-triggered control algorithm for multi-agent systems

In this work a new self-triggered coordination algorithm for multi-agent systems has been proposed. Each agent computes the average of its neighbors' states to update its control input, and then transmits the average state to its neighbors. The self-triggered algorithm is developed by repeatedly computing the event time instants with a set of iterative procedures. Compared with the existing works, the proposed algorithm need less time to achieve consensus. Moreover, significant reduction of the number of triggering events, controller updates and communication transmission can also be achieved.