Non Invasive Identification of Servo Drive Parameters

  • R. Neugebauer
  • A. Hellmich
  • S. Hofmann
  • H. Schlegel
Conference paper


For the tuning of servo controllers as well as for monitoring functions, significant parameters of the controlled system are required. In contrast to identification methods with determined input signals, the paper focuses on the problem of identification with regular process movements (non invasive identification), leading to a lack of power density in some frequency ranges. A nonlinear Least Squares (LS) approach with single mass system and friction characteristic is investigated regarding the accomplishable accuracy and necessary constraints. The proposed method is applicable on industrial motion controllers and has been carried out with a multitude of input sequences. To verify the performance of the approach, achieved experimental results for the model parameters are exposed.


Input Sequence Power Density Spectrum Little Square Problem Friction Characteristic Servo Drive 
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  1. 1.
    O’Dwyer, A.: Handbook of PI and PID Controller Tuning Rules. Imperial College Press (2003)Google Scholar
  2. 2.
    Åström, K.J., Hägglund, T.: Advanced PID Control. ISA, Research Triangle Park (2006)Google Scholar
  3. 3.
    Villwock, S.: Identifikationsmethoden für die automatisierte Inbetriebnahme und Zustandsüberwachung elektrischer Antriebe, Dissertation Thesis, University of Siegen (2007)Google Scholar
  4. 4.
    Bebar, M.: Regelgütebewertung in kontinuierlichen verfahrenstechnischen Anlagen anhand vorliegender Messreihen, Dissertation Thesis, Ruhr-Universität Bochum (2005)Google Scholar
  5. 5.
    Neugebauer, R., et al.: Überwachung und Bewertung von Antriebsregelungen bei Verzicht auf zusätzliche Sensorik. In: VDI-Berichte 2092, pp. 117–120 (2010)Google Scholar
  6. 6.
    Isermann, R.: Identifikation dynamischer Systeme 1. Springer, Heidelberg (1992)zbMATHGoogle Scholar
  7. 7.
    Beineke, S., et al.: Comparison of parameter Identification Schemes for Self-Commissioning Drive Control of Nonlinear Two-Mass Systems. In: IEEE Industry Applications Society, Annual Meeting New Orleans, pp. 493–500 (1997)Google Scholar
  8. 8.
    Beineke, S.: Online-Schätzung von mechanischen Parametern, Kennlinien und Zustandsgrößen geregelter elektrischer Antriebe. VDI Fortschritt-Berichte 816 (2000)Google Scholar
  9. 9.
    Siemens, A.G.: SINAMICS S120/150 Function Manual (2008)Google Scholar
  10. 10.
    Bernecker, Rainer: Industrie Elektronik GmbH. Autotuning ACP 10 Software (2006)Google Scholar
  11. 11.
    Schütte, F.: Automatisierte Reglerinbetriebnahme für elektrische Antriebe mit schwingungsfähiger Mechanik, Dissertation Thesis, Shaker Verlag (2003)Google Scholar
  12. 12.
    Doenitz, S.: Verfahren zur Minimierung des Einflusses von Störkräften in lagegeregelten Vorschubantrieben, Dissertation Thesis, Technische Universität Darmstadt (2003)Google Scholar
  13. 13.
    Burkhard, H.: Applikation von Algorithmen zur Bestimmung von Massenträgheitsmomenten im Umfeld von Bewegungssteuerungen, Diploma Thesis, Chemnitz University of Technology (2010)Google Scholar
  14. 14.
    Wertz, H., Beineke, S., Fröhleke, N.: Computer aided commissioning of speed and position control for electrical drives with identification of mechanical load. In: IEEE Industry Applications Conference (1999)Google Scholar
  15. 15.
    Mink, F., Bähr, A., Beineke, S.: Self-commissioning feedforward control for industrial servo drive. Elektromotion (2009)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • R. Neugebauer
    • 1
  • A. Hellmich
    • 1
  • S. Hofmann
    • 1
  • H. Schlegel
    • 1
  1. 1.Faculty of Mechanical Engineering, Institute for Machine Tools and Production ProcessesChemnitz University of TechnologyChemnitzGermany

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