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Dokumenttyp:
Konferenzbeitrag 
Art des Konferenzbeitrags:
Textbeitrag / Aufsatz 
Autor(en):
Rowold, M.; Wischnewski, A.; Lohmann, B. 
Titel:
Constrained Bayesian Optimization of a Linear Feed-Forward Controller 
Seitenangaben Beitrag:
pp. 1-6 
Abstract:
Models of dynamic systems often contain uncertain parameters or do not describe all dynamics. In some cases, they cannot represent the plants accurately enough, which limits the achievable performance of model-based controller design. Learning-based controllers can adapt to the true parameters and cope with unmodeled dynamics. However, it must be ensured that an adaption does not cause the system to violate its physical or operating constraints, which could result in dangerous situations or harm...    »
 
Stichworte:
bayesian optimization; learning algorithms; learning control; linear flters; non-causal flter; ingnon-parametric regression; parameter optimization 
Dewey-Dezimalklassifikation:
620 Ingenieurwissenschaften 
Kongress- / Buchtitel:
IFAC Workshop on Adaptive and Learning Control Systems, ALCOS [13´th, 2019, Winchester, United Kingdom] 
Kongress / Zusatzinformationen:
IFAC-PapersOnLine 
Band / Teilband / Volume:
Volume 52, Issue 29 
Ausgabe:
Code 141968 
Ausrichter der Konferenz:
IFAC 
Datum der Konferenz:
4. - 6.12.2019 
Verlag / Institution:
Elsevier B.V. 
Jahr:
2019 
Monat:
Dec 
Nachgewiesen in:
Scopus 
Serien-ISSN:
24058963 
Reviewed:
ja 
Sprache:
en 
TUM Einrichtung:
Lehrstuhl für Regelungstechnik