Zusammenfassung
In diesem Beitrag wird eine Methode zum Entwurf von Testsignalen für die Identifikation lokal-affiner dynamischer Takagi-Sugeno-SISO-Modelle vorgestellt. Diese Methode verwendet ein erstes identifiziertes Prozessmodell und nutzt so erlangtes Wissen über die Modellstruktur mittels modellprädiktiver Regelung aus, um einen Testsignalentwurf durchzuführen. Im Rahmen einer Fallstudie wird die Methode demonstriert.
Abstract
In this contribution a test signal design method for the identification of Takagi-Sugeno SISO models is presented. This method uses an initial process model and exploits knowledge about the model structure by using model predictive control. The method is demonstrated in a case study.
Funding source: Deutsche Forschungsgemeinschaft
Award Identifier / Grant number: KR 3795/7-1
Funding statement: Die Forschungsarbeit wurde durch die Deutsche Forschungsgemeinschaft (DFG) unterstützt, Projektnummer KR 3795/7-1.
Über die Autoren
Dipl.-Ing. Matthias Himmelsbach war wissenschaftlicher Mitarbeiter am Fachgebiet Mess- und Regelungstechnik der Universität Kassel. Sein Forschungsschwerpunkt war der Testsignalentwurf für die nichtlineare Systemidentifikation.
Univ.-Prof. Dr.-Ing. Andreas Kroll ist Leiter des Fachgebiets Mess- und Regelungstechnik der Universität Kassel. Seine Forschungsschwerpunkte sind nichtlineare Identifikations- und Regelungsmethoden, Computational Intelligence, Fernmesstechnik und Sensordatenfusion.
Danksagung
Es wird Herrn M. Sc. Frederik Bendt für seinen Beitrag (Wegbasierter Testsignalentwurf für die Identifikation lokal-affiner dynamischer TS-Modelle durch Applikation nichtlinearer MPCs unter Ausnutzung der lokalen Modellstruktur) gedankt. Es wird den Gutachtern für die Anmerkungen und Anregungen gedankt.
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