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020 _a9783658330347
024 7 _a10.1007/978-3-658-33034-7
_2doi
040 _aES-MaUEC
_bspa
_cES-MaUEC
_dES-MaUEC
050 4 _aTJ216
_b2021 EB
100 1 _aHua, Changsheng
_eautor
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_9678619
245 1 0 _aReinforcement learning aided performance optimization of feedback control systems
_cby Changsheng Hua
250 _aFirst edition 2021
264 1 _aWiesbaden
_bSpringer International Publising
_c2021
300 _a1 recurso en línea (XIX, 127 páginas)
_b53 ilustraciones
336 _2rdacontent
_aTexto
_btxt
337 _2rdamedia
_aelectrónico
_bc
338 _2rdacarrier
_arecurso electrónico
_bcr
347 _atext file
_bPDF
_2rda
505 0 _aIntroduction -- 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 3 _aChangsheng 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.
988 _aSpringer_Computer_2021
650 7 _2embne
_aSistemas de control por realimentación
_9145605
710 2 _aSpringerLink
856 4 0 _uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-658-33034-7
_zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942 _2lcc
_cLE
998 _b05/2021
_dz
_eb
_zSI