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Output regulation of unknown linear systems using average cost reinforcement learning
Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
Univ Texas Arlington, TX 76019 USA; Northeastern Univ, Peoples R China.
2019 (engelsk)Inngår i: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 110, artikkel-id 108549Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

In this paper, we introduce an optimal average cost learning framework to solve output regulation problem for linear systems with unknown dynamics. Our optimal framework aims to design the controller to achieve output tracking and disturbance rejection while minimizing the average cost. We derive the Hamilton-Jacobi-Bellman (HJB) equation for the optimal average cost problem and develop a reinforcement algorithm to solve it. Our proposed algorithm is an off-policy routine which learns the optimal average cost solution completely model-free. We rigorously analyze the convergence of the proposed algorithm. Compared to previous approaches for optimal tracking controller design, we elevate the need for judicious selection of the discounting factor and the proposed algorithm can be implemented completely model-free. We support our theoretical results with a simulation example. (C) 2019 Elsevier Ltd. All rights reserved.

sted, utgiver, år, opplag, sider
PERGAMON-ELSEVIER SCIENCE LTD , 2019. Vol. 110, artikkel-id 108549
Emneord [en]
Output regulation; Reinforcement learning; Linear systems; Optimal control
HSV kategori
Identifikatorer
URN: urn:nbn:se:liu:diva-162304DOI: 10.1016/j.automatica.2019.108549ISI: 000495491900011OAI: oai:DiVA.org:liu-162304DiVA, id: diva2:1374082
Merknad

Funding Agencies|Vinnova Competence Center LINK-SIC; Wallenberg Artificial Intelligence, Autonomous Systems and Software Program (WASP)

Tilgjengelig fra: 2019-11-28 Laget: 2019-11-28 Sist oppdatert: 2020-02-19

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Fulltekst tilgjengelig fra 2021-09-16 08:42
Tilgjengelig fra 2021-09-16 08:42

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