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Reinforcement learning aided perform...

Hua, Changsheng.

Reinforcement learning aided performance optimization of feedback control systems

Record Type:	Electronic resources : Monograph/item
Title/Author:	Reinforcement learning aided performance optimization of feedback control systemsby Changsheng Hua.
Author:	Hua, Changsheng.
Published:	Wiesbaden :Springer Fachmedien Wiesbaden :2021.
Description:	xix, 127 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Feedback control systems.
Online resource:	https://doi.org/10.1007/978-3-658-33034-7
ISBN:	9783658330347$q(electronic bk.)

Reinforcement learning aided performance optimization of feedback control systems
Hua, Changsheng.

Reinforcement learning aided performance optimization of feedback control systems[electronic resource] /by Changsheng Hua. - Wiesbaden :Springer Fachmedien Wiesbaden :2021. - xix, 127 p. :ill., digital ;24 cm.

Introduction -- The basics of feedback control systems -- Reinforcement learning and feedback control -- Q-learning aided performance optimization of deterministic systems -- NAC aided performance optimization of stochastic systems -- Conclusion and future work.

Changsheng Hua proposes two approaches, an input/output recovery approach and a performance index-based approach for robustness and performance optimization of feedback control systems. For their data-driven implementation in deterministic and stochastic systems, the author develops Q-learning and natural actor-critic (NAC) methods, respectively. Their effectiveness has been demonstrated by an experimental study on a brushless direct current motor test rig. The author: Changsheng Hua received the Ph.D. degree at the Institute of Automatic Control and Complex Systems (AKS), University of Duisburg-Essen, Germany, in 2020. His research interests include model-based and data-driven fault diagnosis and fault-tolerant techniques.

ISBN: 9783658330347$q(electronic bk.)

Standard No.: 10.1007/978-3-658-33034-7doiSubjects--Topical Terms:

182018
Feedback control systems.

LC Class. No.: TJ216 / .H83 2021

Dewey Class. No.: 629.83

Reinforcement learning aided performance optimization of feedback control systems
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520 $a Changsheng Hua proposes two approaches, an input/output recovery approach and a performance index-based approach for robustness and performance optimization of feedback control systems. For their data-driven implementation in deterministic and stochastic systems, the author develops Q-learning and natural actor-critic (NAC) methods, respectively. Their effectiveness has been demonstrated by an experimental study on a brushless direct current motor test rig. The author: Changsheng Hua received the Ph.D. degree at the Institute of Automatic Control and Complex Systems (AKS), University of Duisburg-Essen, Germany, in 2020. His research interests include model-based and data-driven fault diagnosis and fault-tolerant techniques.
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