Reinforcement Learning Aided Performance Optimization of Feedback Control Systems

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 n...

Full description

Bibliographic Details
Main Author: Hua, Changsheng
Format: eBook
Language:English
Published: Wiesbaden Springer Fachmedien Wiesbaden 2021, 2021
Edition:1st ed. 2021
Subjects:
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
Description
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
Physical Description:XIX, 127 p. 53 illus online resource
ISBN:9783658330347