Journal
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
Volume 63, Issue 10, Pages 3581-3587Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TAC.2018.2799526
Keywords
Adaptive dynamic programming (ADP); leader-to-formation stability (LFS); optimal tracking control; switching network topology
Funding
- U.S. National Science Foundation [ECCS-1501044]
- Mitsubishi Electric Research Laboratories
- China NSFC [61633007]
- ONR [N00014-17-1-2239]
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This note proposes a novel data-driven solution to the cooperative adaptive optimal control problem of leader-follower multiagent systems under switching network topology. The dynamics of all the followers are unknown, and the leader is modeled by a perturbed exosystem. Through the combination of adaptive dynamic programming and internal model principle, an approximate optimal controller is iteratively learned online using real-time input-state data. Rigorous stability analysis shows that the system in closed-loop with the developed control policy is leader-to-formation stable, with guaranteed robustness to unmeasurable leader disturbance. Numerical results illustrate the effectiveness of the proposed data-driven algorithm.
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