Reinforcement Learning Aided Performance Optimization of Feedback Control Systems by Changsheng Hua
Requirements: .ePUB reader, 18.4 MB
Overview: 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.
Genre: Non-Fiction > Tech & Devices
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https://userupload.net/zvh0pr9go8z0
https://dropgalaxy.vip/xn67lzgg12co
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Requirements: .ePUB reader, 18.4 MB
Overview: 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.
Genre: Non-Fiction > Tech & Devices
Download Instructions:
https://userupload.net/zvh0pr9go8z0
https://dropgalaxy.vip/xn67lzgg12co
Trouble downloading? Read This.