Robust control for the systems preceded by hysteresis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Citations (Scopus)

Abstract

Hysteresis hinders the effectiveness of smart materials in sensors and actuators. It is a challenging task to control the systems with hysteresis. This paper discussed the identification of hysteresis described by Prandtl-Ishlinskii model. The control method of hysteresis output is proposed. Then, the robust control for the linear systems preceded with hysteresis is considered. The unknown parameters of the system together with the density function of the hysteresis are adaptively estimated. The robust sliding mode tracking controller is synthesized by using the estimated parameters of the system and the density function of the hysteresis. The output tracking can be approximately achieved by using the proposed controller.

Original languageEnglish
Title of host publicationProceedings of the 25th IASTED International Conference on Modelling, Identification, and Control, MIC 2006
Pages173-178
Number of pages6
Publication statusPublished - 2006 Dec 1
Event25th IASTED International Conference on Modelling, Identification, and Control, MIC 2006 - Lanzarote, Canary Islands, Spain
Duration: 2006 Jan 62006 Jan 8

Publication series

NameProceedings of the IASTED International Conference on Modelling, Identification, and Control, MIC
ISSN (Print)1025-8973

Conference

Conference25th IASTED International Conference on Modelling, Identification, and Control, MIC 2006
CountrySpain
CityLanzarote, Canary Islands
Period06/1/606/1/8

Keywords

  • Adaptive method
  • Hysteresis
  • Robust control

ASJC Scopus subject areas

  • Software
  • Modelling and Simulation
  • Computer Science Applications

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  • Cite this

    Chen, X. (2006). Robust control for the systems preceded by hysteresis. In Proceedings of the 25th IASTED International Conference on Modelling, Identification, and Control, MIC 2006 (pp. 173-178). (Proceedings of the IASTED International Conference on Modelling, Identification, and Control, MIC).