Leader-to-Formation Stability of Multi-Agent Systems: An Adaptive Optimal Control Approach

Authors

Weinan Gao, Georgia Southern UniversityFollow
Zhong-Ping Jiang, Tandon School of EngineeringFollow
Frank L. Lewis, University of Texas at Arlington
Yebin Wang, Mitsubishi Electric Research Labs

Document Type

Article

Publication Date

1-30-2018

Publication Title

IEEE Transactions on Automatic Control

DOI

10.1109/TAC.2018.2799526

ISSN

1558-2523

Abstract

This note proposes a novel data-driven solution to the cooperative adaptive optimal control problem of leader-follower multi-agent 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.

Recommended Citation

Gao, Weinan, Zhong-Ping Jiang, Frank L. Lewis, Yebin Wang. 2018. "Leader-to-Formation Stability of Multi-Agent Systems: An Adaptive Optimal Control Approach." IEEE Transactions on Automatic Control: 1: IEEE Xplore. doi: 10.1109/TAC.2018.2799526
https://digitalcommons.georgiasouthern.edu/electrical-eng-facpubs/119