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Reinforcement Learning Aided Performance Optimization of Feedback Control Systems / by Changsheng Hua.

SpringerLink Books Computer Science (2011-2024) Available online

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Format:
Book
Author/Creator:
Hua, Changsheng, Author.
Contributor:
SpringerLink (Online service)
Series:
Computer Science (SpringerNature-11645)
Language:
English
Subjects (All):
Machine learning.
Computers.
Computer input-output equipment.
Electronic digital computers-Evaluation.
Machine Learning.
Hardware Performance and Reliability.
Input/Output and Data Communications.
System Performance and Evaluation.
Local Subjects:
Machine Learning.
Hardware Performance and Reliability.
Input/Output and Data Communications.
System Performance and Evaluation.
Physical Description:
1 online resource (XIX, 127 pages) : 53 illustrations
Edition:
1st ed. 2021.
Contained In:
Springer Nature eBook
Place of Publication:
Wiesbaden : Springer Fachmedien Wiesbaden : Imprint: Springer Vieweg, 2021.
System Details:
text file PDF
Summary:
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.
Contents:
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.
Other Format:
Printed edition:
ISBN:
978-3-658-33034-7
9783658330347
Access Restriction:
Restricted for use by site license.

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