TY - GEN
T1 - Physics-based modelling of a piezoelectric actuator using genetic algorithm
AU - Miri, Narges
AU - Mohammadzaheri, Morteza
AU - Chen, Lei
AU - Grainger, Steven
AU - Bazghaleh, Mohsen
PY - 2013
Y1 - 2013
N2 - 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.
AB - 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.
KW - Optimisation method
KW - Piezoelectric actuator
KW - Voigt model
KW - displacement estimation
KW - genetic algorithm
KW - physics-based models
KW - sampling time
UR - http://www.scopus.com/inward/record.url?scp=84897689370&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84897689370&partnerID=8YFLogxK
U2 - 10.1109/ISIEA.2013.6738960
DO - 10.1109/ISIEA.2013.6738960
M3 - Conference contribution
AN - SCOPUS:84897689370
SN - 9781479911257
T3 - ISIEA 2013 - 2013 IEEE Symposium on Industrial Electronics and Applications
SP - 16
EP - 20
BT - ISIEA 2013 - 2013 IEEE Symposium on Industrial Electronics and Applications
T2 - 2013 IEEE Symposium on Industrial Electronics and Applications, ISIEA 2013
Y2 - 22 September 2013 through 25 September 2013
ER -