Finite-Time Consensus for Linear Multi-Agent Systems Using Data-Driven Terminal ILC

In this brief, the finite time consensus problem for a class of unknown linear multi-agent systems is considered. Firstly, a linear mapping relationship between the agent's terminal output and the control input along the iteration domain is established. Then, a novel distributed data-driven iterative learning consensus protocol is constructed only using the I/O data of each agent and its neighbors. Meanwhile, a convergence condition that does not depend on model information is derived for the multi-agent system. It is shown that the proposed protocol can guarantee that all agents achieve the finite-time consensus objective. Finally, an example of numerical simulation is given to verify the effectiveness of the proposed design.