Control of Hysteresis: Theory and Experimental Results

Abstract

Hysteresis in smart materials hinders the wider applicability of such materials in actuators. In this paper, a systematic approach for coping with hysteresis is presented. The method is illustrated through the example of controlling a commercially available magnetostrictive actuator. We utilize the low-dimensional model for the magnetostrictive actuator that was developed in earlier work. For low frequency inputs, the model approximates to a rate-independent hysteresis operator, with current as its input and magnetization as its output. Magnetostrictive strain is proportional to the square of the magnetization. In this paper, we use a classical Preisach operator for the rate-independent hysteresis operator. In this paper, we present the results of experiments conducted on a commercial magnetostrictive actuator, the purpose of which was the control of the displacement/strain output. A constrained least-squares algorithm is employed to identify a discrete approximation to the Preisach measure. We then discuss a nonlinear inversion algorithm for the resulting Preisach operator, based on the theory of strictly-increasing operators. This algorithm yields a control input signal to produce a desired magnetostrictive response. The effectiveness of the inversion scheme is demonstrated via an open-loop trajectory tracking experiment.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2001
Accession Number
ADA439786

Entities

People

  • P.S.Krishnaprasad
  • Ram Venkataraman
  • Xiaobo Tan

Organizations

  • University of Maryland

Tags

Communities of Interest

  • Air Platforms
  • C4I

DTIC Thesaurus Topics

  • Actuators
  • Algorithms
  • Boundaries
  • Domain Walls
  • Electronic Mail
  • Engineering
  • Equations
  • Errors
  • Ferromagnetic Materials
  • Frequency
  • Hysteresis
  • Identification
  • Least Squares Method
  • Magnetic Fields
  • Magnetic Properties
  • Magnetization
  • Materials

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Materials Science and Engineering.