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Control of Parameter-dependent High-order Systems using Parametric Model Reduction

Regelung parameterabhängiger, hochdimensionaler Systeme mittels parametrischer Modellreduktion
  • Matthias Geuß

    Dipl.-Ing. Matthias Geuß is a research assistant at the Institute of Automatic Control of the Faculty of Mechanical Engineering at the Technische Universität München. His field of research includes parametric model order reduction by matrix interpolation, model predictive control and switched systems.

    Institute of Automatic Control, Faculty of Mechanical Engineering, Technische Universität München, Boltzmannstr. 15, D-85748 Garching bei München, Germany, Phone: +49-(0)89-289-15654

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    , Cholwoo Choi

    Cholwoo Choi, M.Sc. is a former M.Sc. candidate at the Institute of Automatic Control of the Faculty of Mechanical Engineering at the Technische Universität München. His research interest includes parametric model order reduction by matrix interpolation and model predictive control.

    Institute of Automatic Control, Faculty of Mechanical Engineering, Technische Universität München, Boltzmannstr. 15, D-85748 Garching bei München, Germany

    and Boris Lohmann

    Prof. Dr.-Ing. habil. Boris Lohmann is Head of the Institute of Automatic Control of the Faculty of Mechanical Engineering at the Technische Universität München. His research activities include model order reduction, nonlinear, robust and optimal control as well as active vibration control.

    Institute of Automatic Control, Faculty of Mechanical Engineering, Technische Universität München, Boltzmannstr. 15, D-85748 Garching bei München, Germany, Fax: +49-(0)89-289-15653

Abstract

In this paper controllers and observers are designed for high-dimensional parameter-dependent LTI systems. The application of parametric model order reduction by matrix interpolation is proposed in order to use common methods of control. In the offline phase, the parameter space is sampled and a set of locally reduced systems is obtained using projection-based model order reduction, which results in a database of system matrices. In the online phase, a reduced system can be calculated for a desired parameter vector by interpolating the system matrices from the database. Controllers and observers can be obtained for the interpolated system using common methods of control design. The approach is demonstrated through a practical example on a test rig for a gantry crane operating with different loads.

Zusammenfassung

In diesem Beitrag werden Regler und Beobachter für hochdimensionale, parameterabhängige Systeme bestimmt. Um gängige Verfahren zur Regler- bzw. Beobachterauslegung nutzen zu können, wird die Anwendung von parametrischer Modellreduktion basierend auf Matrixinterpolation vorgeschlagen. In der Offline-Phase wird für ein Raster des Parameterraums eine Menge von lokal reduzierten Systemen mittels projektionsbasierter Modellreduktion berechnet, was eine Datenbasis von Systemmatrizen ergibt. In der Online-Phase erhält man das reduzierte Modell für einen gewünschten Parametervektor durch Interpolation der Systemmatrizen der Datenbasis. Für das interpolierte System können dann mit den gängigen Verfahren der Regelungstechnik Regler bzw. Beobachter ausgelegt werden. Die Methode wird durch ein praktisches Beispiel an einem Prüfstand, der das Verhalten eines Brückenkrans mit unterschiedlichen Lastmassen nachbilden soll, unterstützt.

About the authors

Matthias Geuß

Dipl.-Ing. Matthias Geuß is a research assistant at the Institute of Automatic Control of the Faculty of Mechanical Engineering at the Technische Universität München. His field of research includes parametric model order reduction by matrix interpolation, model predictive control and switched systems.

Institute of Automatic Control, Faculty of Mechanical Engineering, Technische Universität München, Boltzmannstr. 15, D-85748 Garching bei München, Germany, Phone: +49-(0)89-289-15654

Cholwoo Choi

Cholwoo Choi, M.Sc. is a former M.Sc. candidate at the Institute of Automatic Control of the Faculty of Mechanical Engineering at the Technische Universität München. His research interest includes parametric model order reduction by matrix interpolation and model predictive control.

Institute of Automatic Control, Faculty of Mechanical Engineering, Technische Universität München, Boltzmannstr. 15, D-85748 Garching bei München, Germany

Boris Lohmann

Prof. Dr.-Ing. habil. Boris Lohmann is Head of the Institute of Automatic Control of the Faculty of Mechanical Engineering at the Technische Universität München. His research activities include model order reduction, nonlinear, robust and optimal control as well as active vibration control.

Institute of Automatic Control, Faculty of Mechanical Engineering, Technische Universität München, Boltzmannstr. 15, D-85748 Garching bei München, Germany, Fax: +49-(0)89-289-15653

Received: 2014-2-22
Accepted: 2014-4-23
Published Online: 2014-6-28
Published in Print: 2014-7-28

©2014 Walter de Gruyter Berlin/Boston

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