Adaptive Dynamic Programming: Solltrajektorienfolgeregelung und Konvergenzbedingungen

In this work, discrete-time and continuous-time methods that integrate flexible reference trajectory representations into Adaptive Dynamic Programming approaches are presented and analyzed for the first time. Moreover, theoretical conditions on the system state are derived that ensure the persistent...

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Auteur principal: Köpf, Florian
Format: Online
Langue:allemand
Publié: KIT Scientific Publishing 2022
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Accès en ligne:OCN: 1367234043
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author Köpf, Florian
author_browse Köpf, Florian
author_facet Köpf, Florian
author_sort Köpf, Florian
collection Directory of Open Access Books
description In this work, discrete-time and continuous-time methods that integrate flexible reference trajectory representations into Adaptive Dynamic Programming approaches are presented and analyzed for the first time. Moreover, theoretical conditions on the system state are derived that ensure the persistent excitation property, which is crucial for the convergence of the adaptation. Real-world applications of the presented adaptive optimal trajectory tracking control methods reveal their potential.
format Online
id doab-20.500.12854ir-93695
institution Directory of Open Access Books
language ger
publishDate 2022
publishDateRange 2022
publishDateSort 2022
publisher KIT Scientific Publishing
publisherStr KIT Scientific Publishing
record_format ojs
spelling doab-20.500.12854ir-936952025-05-27T08:01:59Z Adaptive Dynamic Programming: Solltrajektorienfolgeregelung und Konvergenzbedingungen Köpf, Florian Adaptive Dynamic Programming (ADP); Reinforcement Learning (RL); Persistent Excitation (PE); adaptive Optimalregelung; lernende Regler; KI; Adaptive Optimal Control; Learning-Based Control; AI thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TH Energy technology and engineering::THR Electrical engineering In this work, discrete-time and continuous-time methods that integrate flexible reference trajectory representations into Adaptive Dynamic Programming approaches are presented and analyzed for the first time. Moreover, theoretical conditions on the system state are derived that ensure the persistent excitation property, which is crucial for the convergence of the adaptation. Real-world applications of the presented adaptive optimal trajectory tracking control methods reveal their potential. 2022-11-15T04:04:22Z 2022-11-15T04:04:22Z 2022-11-14T14:28:27Z 2022 book OCN: 1367234043 https://library.oapen.org/handle/20.500.12657/59238 9783731511939 https://directory.doabooks.org/handle/20.500.12854/93695 ger Karlsruher Beiträge zur Regelungs- und Steuerungstechnik open access image/jpeg image/jpeg image/jpeg image/jpeg image/jpeg Attribution-ShareAlike 4.0 International Attribution-ShareAlike 4.0 International Attribution-ShareAlike 4.0 International Attribution-ShareAlike 4.0 International Attribution-ShareAlike 4.0 International https://library.oapen.org/bitstream/20.500.12657/59238/1/adaptive-dynamic-programming-solltrajektorienfolgeregelung-und-konvergenzbedingungen.pdf https://library.oapen.org/bitstream/20.500.12657/59238/1/adaptive-dynamic-programming-solltrajektorienfolgeregelung-und-konvergenzbedingungen.pdf https://library.oapen.org/bitstream/20.500.12657/59238/1/adaptive-dynamic-programming-solltrajektorienfolgeregelung-und-konvergenzbedingungen.pdf https://library.oapen.org/bitstream/20.500.12657/59238/1/adaptive-dynamic-programming-solltrajektorienfolgeregelung-und-konvergenzbedingungen.pdf https://library.oapen.org/bitstream/20.500.12657/59238/1/adaptive-dynamic-programming-solltrajektorienfolgeregelung-und-konvergenzbedingungen.pdf KIT Scientific Publishing 10.5445/KSP/1000145970 10.5445/KSP/1000145970 68fffc18-8f7b-44fa-ac7e-0b7d7d979bd2 9783731511939 AG Universitätsverlage 304 open access
spellingShingle Adaptive Dynamic Programming (ADP); Reinforcement Learning (RL); Persistent Excitation (PE); adaptive Optimalregelung; lernende Regler; KI; Adaptive Optimal Control; Learning-Based Control; AI
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TH Energy technology and engineering::THR Electrical engineering
Köpf, Florian
Adaptive Dynamic Programming: Solltrajektorienfolgeregelung und Konvergenzbedingungen
title Adaptive Dynamic Programming: Solltrajektorienfolgeregelung und Konvergenzbedingungen
title_full Adaptive Dynamic Programming: Solltrajektorienfolgeregelung und Konvergenzbedingungen
title_fullStr Adaptive Dynamic Programming: Solltrajektorienfolgeregelung und Konvergenzbedingungen
title_full_unstemmed Adaptive Dynamic Programming: Solltrajektorienfolgeregelung und Konvergenzbedingungen
title_short Adaptive Dynamic Programming: Solltrajektorienfolgeregelung und Konvergenzbedingungen
title_sort adaptive dynamic programming solltrajektorienfolgeregelung und konvergenzbedingungen
topic Adaptive Dynamic Programming (ADP); Reinforcement Learning (RL); Persistent Excitation (PE); adaptive Optimalregelung; lernende Regler; KI; Adaptive Optimal Control; Learning-Based Control; AI
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TH Energy technology and engineering::THR Electrical engineering
topic_facet Adaptive Dynamic Programming (ADP); Reinforcement Learning (RL); Persistent Excitation (PE); adaptive Optimalregelung; lernende Regler; KI; Adaptive Optimal Control; Learning-Based Control; AI
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TH Energy technology and engineering::THR Electrical engineering
url OCN: 1367234043
work_keys_str_mv AT kopfflorian adaptivedynamicprogrammingsolltrajektorienfolgeregelungundkonvergenzbedingungen