Abstract
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.
| Original language | English (US) |
|---|---|
| Article number | 8272371 |
| Pages (from-to) | 3581-3587 |
| Number of pages | 7 |
| Journal | IEEE Transactions on Automatic Control |
| Volume | 63 |
| Issue number | 10 |
| DOIs | |
| State | Published - Oct 2018 |
Keywords
- Adaptive dynamic programming (ADP)
- leader-to-formation stability (LFS)
- optimal tracking control
- switching network topology
ASJC Scopus subject areas
- Control and Systems Engineering
- Computer Science Applications
- Electrical and Electronic Engineering
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Cite this
Gao, W., Jiang, Z. P., Lewis, F. L., & Wang, Y. (2018). Leader-to-Formation Stability of Multiagent Systems: An Adaptive Optimal Control Approach. IEEE Transactions on Automatic Control, 63(10), 3581-3587. [8272371]. https://doi.org/10.1109/TAC.2018.2799526