Abstract
In this paper, a distributed model predictive control (DMPC) is proposed for static formation of unconstrained double-integrator multiagent systems. The formation problem is formulated in the leader-follower framework, where the leaders have access to both their own and relative neighboring information, and the followers only have access to relative neighboring information. In the process of optimization, only current relative information is communicated between neighboring agents. For each agent, its predicted control vector and neighboring control vectors are regarded as decision variables for optimization, but only the own optimized current control of the agent is implemented. An analytical solution to the DMPC is obtained, and new sufficient conditions are given for achieving the static formation.
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 callDisclaimer: 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.
