Advertisement

Adaptive Control of Time-Varying and Nonlinear Systems Using a Multi-Model Approach

  • H. Unbehauen
Part of the Progress in Systems and Control Theory book series (PSCT, volume 6)

Abstract

This paper describes the application of a self-tuning controller to uncertain systems whose parameters are changing very rapidly, for example due to rapid changes of the operating conditions. Classical adaptive controllers are not appropriate for rapid parameter changes of the controlled process. The technique presented in this paper is based on the description of a nonlinear or time-varying system by a multi-model consisting of several linear submodels. Each submodel describes the system at one operating condition. The parameters of the submodels have to be estimated on-line. A statistical test method is applied for the fast detection of parameter changes. For the design of the self-tuning controller an LQG-approach has been applied.

Keywords

Adaptive Control Parameter Vector Operating Point Equation Error Uncertain System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Anderson, P. (1985). Adaptive forgetting in recursive identification through multiple models. International Journal of Control 42, pp. 1175–1194.CrossRefGoogle Scholar
  2. Aström, K. and B. Wittenmark (1984). Computer controlled systems. Prentice-Hall, Englewood Cliffs.Google Scholar
  3. Bertin, D. (1986). Tracking of nonstationary systems by means of different prediction-error directional forgetting techniques. Proceed. IFAC Workshop on Adaptive systems in Control and Signal Processing, Lund, Sweden pp. 91–96.Google Scholar
  4. Diekmann K. and H. Unbehauen (1985). On-line parameter estimation in a class of nonlinear systems via modified least-squares. 7th IFAC-symposium on `Identification and systems Parameter Estimation’ York, pp. 149–153.Google Scholar
  5. Fortescue T., L. Kershenbaum and B. Ydstie (1981). Implementation of self-tuning regulators with variable forgetting factors. Automatica 17 pp. 831–835.CrossRefGoogle Scholar
  6. Jedner U. (1988). Eine adaptive Regelstrategie für zeitvariante und nichtlineare Systeme. Dissertation Ruhr-Universität Bochum. Fortschritt-Berichte VDI-Reihe 8 No. 167 VDI-Verlag Düsseldorf.Google Scholar
  7. Jedner, U. and H. Unbehauen (1988). Erkennung von Betriebszuständen einer Anlage mit Hilfe eines statistischen Testverfahrens. Automatisierungstechnik at 36, pp. 289–294.Google Scholar
  8. Jedner U. and H. Unbehauen (1989). Intelligent adaptive control for a class of time-varying systems. In Borne P. (Ed.): Computing and computers for control systems. I. C. Baltzer AG, Scientific Publishing Co. ( IMACs ), pp. 123–126.Google Scholar
  9. Kucera V. (1979). Discrete linear control. John Wiley ttt Sons Chichester, New York, Brisbane, Toronto.Google Scholar
  10. Kulhavy, R. and M. Karny (1984). Tracking of slowly varying parameters by directional forgetting. Proc. 9th IFAC World Congress Budapest, Vol. 10, pp. 79–83.Google Scholar
  11. Unbehauen H. and U. Jedner (1986). Multimodellansatz zur Identifikation von Regelstrecken mit schnellen Parameteränderungen. Zeitschrift für messen steuern, regeln (msr) 29, pp. 218–220.Google Scholar
  12. Unbehauen, H. (1988). Regelungstechnik III ( 3. Auflage ), Vieweg-Verlag Wiesbaden/Braunschweig.Google Scholar

Copyright information

© Springer Science+Business Media New York 1990

Authors and Affiliations

  • H. Unbehauen
    • 1
  1. 1.Dept. of Electrical EngineeringRuhr-University BochumBochum 1Germany

Personalised recommendations