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  4. System identification of a hysteresis-controlled pump system using SINDy
 
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2020
Conference Paper
Title

System identification of a hysteresis-controlled pump system using SINDy

Abstract
Hysteresis-controlled devices are widely used in industrial applications. For example, cooling devices usually contain a two-point controller, resulting in a nonlinear hybrid system with two discrete states. Dynamic models of systems are essential for optimizing such industrial supply technology. However, conventional system identification approaches can hardly handle hysteresis-controlled devices. Thus, the new identification method Sparse Identification of Nonlinear Dynamics (SINDy) is extended to consider hybrid systems. SINDy composes models from basis functions out of a customized library in a data-driven manner. For modeling systems that behave dependent on their own past as in the case of natural hysteresis, Ferenc Preisach introduced the relay hysteron as an elementary mathematical description. In this new method (SINDyHybrid), tailored basis functions in form of relay hysterons are added to the library which is used by SINDy. Experiments with a hysteresis controlled water basin show that this approach correctly identifies state transitions of hybrid systems and also succeeds in modeling the dynamics of the discrete system states. A novel proximity hysteron achieves the robustness of this method. The impacts of the sampling rate and the signal noise ratio of the measurement data are examined accordingly.
Author(s)
Thiele, Gregor
Fraunhofer-Institut für Produktionsanlagen und Konstruktionstechnik IPK  
Fey, Arne
Fraunhofer-Institut für Produktionsanlagen und Konstruktionstechnik IPK
Sommer, David
Weierstrass Institute for Applied Analysis and Stochastics, Berlin
Krüger, Jörg  
Fraunhofer-Institut für Produktionsanlagen und Konstruktionstechnik IPK  
Mainwork
24th International Conference on System Theory, Control and Computing, ICSTCC 2020. Proceedings  
Project(s)
EnEffReg
Funder
Bundesministerium für Wirtschaft und Energie BMWi (Deutschland)  
Conference
International Conference on System Theory, Control and Computing (ICSTCC) 2020  
Open Access
DOI
10.1109/ICSTCC50638.2020.9259776
Language
English
Fraunhofer-Institut für Produktionsanlagen und Konstruktionstechnik IPK  
Keyword(s)
  • Autoregressive processes

  • Magnetic hysteresis

  • Biological system modeling

  • Nonlinear dynamical systems

  • Hysteresis

  • Relays

  • Data models

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