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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: IEEE Transactions on Circuits and Systems II: Express Briefs
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
