Abstract
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.
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More From: IEEE Transactions on Circuits and Systems II: Express Briefs
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