Cooperative and adaptive optimal output regulation of discrete-time multi-agent systems using reinforcement learning

Weinan Gao, Yiyang Liu, Adedapo Odekunle, Zhong Ping Jiang, Yunjun Yu, Pingli Lu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper proposes an original data-driven intelligent control solution to the cooperative output regulation problem of discrete-time multi-agent systems. Based on the combination of internal model principle and reinforcement learning, a distributed suboptimal controller is learned realtime via online input-state data collected from system trajectories. Rigorous theoretical analysis guarantees the convergence of the proposed algorithm and the asymptotic stability of the closed-loop system. Numerical results validate the effectiveness of the proposed control methodology.

Original languageEnglish (US)
Title of host publication2018 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages348-353
Number of pages6
ISBN (Electronic)9781538668689
DOIs
StatePublished - Jan 22 2019
Event2018 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2018 - Kandima, Maldives
Duration: Aug 1 2018Aug 5 2018

Publication series

Name2018 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2018

Conference

Conference2018 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2018
CountryMaldives
CityKandima
Period8/1/188/5/18

ASJC Scopus subject areas

  • Artificial Intelligence
  • Control and Optimization

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    Gao, W., Liu, Y., Odekunle, A., Jiang, Z. P., Yu, Y., & Lu, P. (2019). Cooperative and adaptive optimal output regulation of discrete-time multi-agent systems using reinforcement learning. In 2018 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2018 (pp. 348-353). [8621852] (2018 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/RCAR.2018.8621852