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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Hoofdauteur: Köpf, Florian (auth)
Formaat: Elektronisch Hoofdstuk
Gepubliceerd in: KIT Scientific Publishing 2022
Reeks:Karlsruher Beiträge zur Regelungs- und Steuerungstechnik
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DOAB: description of the publication
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245 1 0 |a Adaptive Dynamic Programming: Solltrajektorienfolgeregelung und Konvergenzbedingungen 
260 |b KIT Scientific Publishing  |c 2022 
300 |a 1 electronic resource (304 p.) 
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520 |a 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. 
540 |a Creative Commons  |f https://creativecommons.org/licenses/by-sa/4.0/  |2 cc  |4 https://creativecommons.org/licenses/by-sa/4.0/ 
546 |a German 
650 7 |a Electrical engineering  |2 bicssc 
653 |a Adaptive Dynamic Programming (ADP); Reinforcement Learning (RL); Persistent Excitation (PE); adaptive Optimalregelung; lernende Regler; KI; Adaptive Optimal Control; Learning-Based Control; AI 
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856 4 0 |a www.oapen.org  |u https://directory.doabooks.org/handle/20.500.12854/93695  |7 0  |z DOAB: description of the publication