Reinforcement learning aided performance optimization of feedback control systems [electronic resource] / Changsheng Hua.

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Reinforcement learning aided performance optimization of feedback control systems [electronic resource] / Changsheng Hua.

9783658330347 (electronic bk.)
3658330341 (electronic bk.)
9783658330330 (print)
3658330333 (print)

Wiesbaden : Springer Vieweg, 2021.

English

1 online resource (139 pages)

10.1007/978-3-658-33034-7 doi

TJ216

629.8/3

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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