Leader-to-Formation Stability of Multi-Agent Systems

An Adaptive Optimal Control Approach

Weinan Gao, Zhong-Ping Jiang, Frank L. Lewis, Yebin Wang

Research output: Contribution to journalArticle

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.

Original languageEnglish (US)
JournalIEEE Transactions on Automatic Control
DOIs
StateAccepted/In press - Jan 29 2018

Fingerprint

Multi agent systems
Switching networks
Dynamic programming
Topology
Controllers

Keywords

  • Adaptation models
  • Adaptive dynamic programming (ADP)
  • Leader-to-formation stability
  • Mathematical model
  • Multi-agent systems
  • Optimal control
  • Optimal tracking control
  • Stability analysis
  • Switches
  • Switching network topology

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

Cite this

Leader-to-Formation Stability of Multi-Agent Systems : An Adaptive Optimal Control Approach. / Gao, Weinan; Jiang, Zhong-Ping; Lewis, Frank L.; Wang, Yebin.

In: IEEE Transactions on Automatic Control, 29.01.2018.

Research output: Contribution to journalArticle

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