Title

Disturbance Rejection of Multi-Agent Systems: A Reinforcement Learning Differential Game Approach

Abstract

Distributed tracking control of multi-agent linear systems in the presence of disturbances is considered in this paper. The given problem is first formulated into a multi-player zero-sum differential graphical game. It is shown that the solution to this problem requires solving the coupled Hamilton-Jacobi-Isaacs (HJI) equations. A multi-agent reinforcement learning algorithm is developed to find the solution to these coupled HJI equations. The convergence of this algorithm to the optimal solution is proven. It is also shown that the proposed method guarantees L2-bounded synchronization errors in the presence of dynamical disturbances.

Meeting Name

American Control Conference (ACC) (2015: Jul. 1-3, Chicago, IL)

Department(s)

Electrical and Computer Engineering

Keywords and Phrases

Disturbance Rejection; Learning Algorithms; Linear Systems; Reinforcement Learning; Differential Games; Distributed Tracking; Graphical Games; Hamilton-Jacobi-Isaacs; Multi Agent; Multi-Agent Reinforcement Learning; Optimal Solutions; Synchronization Error; Multi Agent Systems

International Standard Book Number (ISBN)

9781479986842

International Standard Serial Number (ISSN)

0743-1619

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2015 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

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