Physics-based modelling of a piezoelectric actuator using genetic algorithm

Narges Miri, Morteza Mohammadzaheri, Lei Chen, Steven Grainger, Mohsen Bazghaleh

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

7 Citations (Scopus)


A number of models have been presented to estimate the displacement of piezoelectric actuators; these models remove the need for accurate displacement sensors used in nanopositioning. Physics based models, inspired by physical phenomena, are widely used for this purpose due to their accuracy and comparatively low number of parameters. The common issue of these models is the lack of a non-ad-hoc and reliable method to estimate their parameters. Parameter identification of a widely accepted physics-based model, introduced by Voigt, is addressed in this paper. Non-linear governing equation of this model consists of five parameters needing to be identified. This research aims at developing/adopting an optimal and standard (non-ad-hoc) parameter identification algorithm to accurately determine the parameters of the model and, in a more general view, all physics-based models of piezoelectric actuators. In this paper, Genetic Algorithm (GA) which is a global optimisation method is employed to identify the model parameters.

Original languageEnglish
Title of host publication2013 IEEE Symposium on Industrial Electronics & Applications
Number of pages5
ISBN (Electronic)9781479911257
Publication statusPublished - 13 Feb 2014
Event2013 IEEE Symposium on Industrial Electronics and Applications - Kuching, Malaysia
Duration: 22 Sept 201325 Sept 2013


Conference2013 IEEE Symposium on Industrial Electronics and Applications
Abbreviated titleISIEA 2013


  • displacement estimation
  • genetic algorithm
  • Optimisation method
  • physics-based models
  • Piezoelectric actuator
  • sampling time
  • Voigt model

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


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