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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| Format: | Online |
| Langue: | allemand |
| Publié: |
KIT Scientific Publishing
2022
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| Sujets: | |
| Accès en ligne: | OCN: 1367234043 |
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| _version_ | 1869527339025563648 |
|---|---|
| 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 |