國立虎尾科技大學 |

Reinforcement Learning Aided Performance Optimization of Feedback Control Systems

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Reinforcement Learning Aided Performance Optimization of Feedback Control Systems/ by Changsheng Hua.
作者:	Hua, Changsheng.
面頁冊數:	XIX, 127 p. 53 illus.online resource. :
Contained By:	Springer Nature eBook
標題:	System Performance and Evaluation. -
電子資源:	https://doi.org/10.1007/978-3-658-33034-7
ISBN:	9783658330347

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. - 1st ed. 2021. - XIX, 127 p. 53 illus.online resource.

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

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

669346
System Performance and Evaluation.

LC Class. No.: Q325.5-.7

Dewey Class. No.: 006.31

Reinforcement Learning Aided Performance Optimization of Feedback Control Systems
LDR:02332nam a22003975i 4500 001 1046526
003 DE-He213
005 20210624110721.0
007 cr nn 008mamaa
008 220103s2021 gw | s |||| 0|eng d
020 $a 9783658330347 $9 978-3-658-33034-7
024 7 $a 10.1007/978-3-658-33034-7 $2 doi
035 $a 978-3-658-33034-7
050 4 $a Q325.5-.7
050 4 $a TK7882.P3
072 7 $a UYQM $2 bicssc
072 7 $a COM004000 $2 bisacsh
072 7 $a UYQM $2 thema
082 0 4 $a 006.31 $2 23
100 1 $a Hua, Changsheng. $e author. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1350084
245 1 0 $a Reinforcement Learning Aided Performance Optimization of Feedback Control Systems $h [electronic resource] / $c by Changsheng Hua.
250 $a 1st ed. 2021.
264 1 $a Wiesbaden : $b Springer Fachmedien Wiesbaden : $b Imprint: Springer Vieweg, $c 2021.
300 $a XIX, 127 p. 53 illus. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
505 0 $a 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.
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.
650 2 4 $a System Performance and Evaluation. $3 669346
650 2 4 $a Input/Output and Data Communications. $3 669873
650 2 4 $a Computer Hardware. $3 669779
650 1 4 $a Machine Learning. $3 1137723
650 0 $a Computer system failures. $3 782237
650 0 $a Input-output equipment (Computers). $3 1254918
650 0 $a Computer hardware. $3 1069242
650 0 $a Machine learning. $3 561253
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783658330330
776 0 8 $i Printed edition: $z 9783658330354
856 4 0 $u https://doi.org/10.1007/978-3-658-33034-7
912 $a ZDB-2-SCS
912 $a ZDB-2-SXCS
950 $a Computer Science (SpringerNature-11645)
950 $a Computer Science (R0) (SpringerNature-43710)