Bernhard, Sebastian ; Adamy, Jürgen (2018)
LQ Optimal Tracking with Unbounded Cost for Unknown Dynamics: An Adaptive Dynamic Programming Approach.
16th European Control Conference. Limassol, Zypern (12.06.2018-15.06.2018)
doi: 10.23919/ECC.2018.8550391
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
In case of unknown system dynamics, we consider linear quadratic optimal tracking on infinite horizons with generally unbounded cost. For the first time, we deal with this problem in the framework of adaptive dynamic programming. So far, existing methods require bounded costs which essentially limits the applicability and achievable performance. Thus, we develop a new algorithm that yields a strongly overtaking optimal control which is an adequate solution. After collecting measurement data in an exploration phase, the algorithm implicitly solves the necessary and sufficient algebraic equations in [3], but without knowledge of the dynamics. Then, implementing the control results in an optimal transition to an optimal stationary trajectory. A simulation example of almost exact tracking for an over-actuated system demonstrates a highly efficient saving of input-energy in contrast to state-of-the-art approaches.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2018 |
| Autor(en): | Bernhard, Sebastian ; Adamy, Jürgen |
| Art des Eintrags: | Bibliographie |
| Titel: | LQ Optimal Tracking with Unbounded Cost for Unknown Dynamics: An Adaptive Dynamic Programming Approach |
| Sprache: | Englisch |
| Publikationsjahr: | 29 November 2018 |
| Verlag: | IEEE |
| Buchtitel: | 2018 European Control Conference (ECC) |
| Veranstaltungstitel: | 16th European Control Conference |
| Veranstaltungsort: | Limassol, Zypern |
| Veranstaltungsdatum: | 12.06.2018-15.06.2018 |
| DOI: | 10.23919/ECC.2018.8550391 |
| Kurzbeschreibung (Abstract): | In case of unknown system dynamics, we consider linear quadratic optimal tracking on infinite horizons with generally unbounded cost. For the first time, we deal with this problem in the framework of adaptive dynamic programming. So far, existing methods require bounded costs which essentially limits the applicability and achievable performance. Thus, we develop a new algorithm that yields a strongly overtaking optimal control which is an adequate solution. After collecting measurement data in an exploration phase, the algorithm implicitly solves the necessary and sufficient algebraic equations in [3], but without knowledge of the dynamics. Then, implementing the control results in an optimal transition to an optimal stationary trajectory. A simulation example of almost exact tracking for an over-actuated system demonstrates a highly efficient saving of input-energy in contrast to state-of-the-art approaches. |
| Fachbereich(e)/-gebiet(e): | 18 Fachbereich Elektrotechnik und Informationstechnik 18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Automatisierungstechnik und Mechatronik 18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Automatisierungstechnik und Mechatronik > Regelungsmethoden und Robotik (ab 01.08.2022 umbenannt in Regelungsmethoden und Intelligente Systeme) |
| Hinterlegungsdatum: | 26 Jul 2018 10:56 |
| Letzte Änderung: | 04 Apr 2023 07:17 |
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