### Abstract

Piezoelectric actuators are the foremost actuators in the area of nanopositioning. However, the sensors employed to measure the actuator displacement are expensive and difficult, if not impossible, to use. Mathematical models can map the easy-to-measure electrical signals to the displacements of the actuators as the displacement sensors are replaced with the models. In addition, these models can be used in model-based control system design. Two main groups of mathematical models are used for this purpose: black box and physics-based models. As an advantage, the latter has a much smaller number of parameters reducing computational demand in real-time applications. However, physics-based models suffer from (1) the relatively low accuracy of the models and (2) non-standard and ad-hoc parameter identification methods. In this research, to improve the model accuracy, mathematical structure of a well-known physics-based model, the Voigt model, is enhanced by adding two complementary terms inspired by another model, the Preisach model. Then, a standard method based on the evolutionary algorithms is proposed to identify the model's parameters. The proposed ideas are substantiated to increase the applicability and accuracy of the model, and they are easily extendable to other physics-based models of piezoelectric actuators. The newly proposed enhanced structure of the Voigt model doubles the estimation accuracy of the original model and results in accuracies comparable with black box models.

Original language | English |
---|---|

Pages (from-to) | 1442-1451 |

Number of pages | 10 |

Journal | Journal of Intelligent Material Systems and Structures |

Volume | 26 |

Issue number | 11 |

DOIs | |

Publication status | Published - Jul 3 2015 |

### Fingerprint

### Keywords

- actuator
- control
- optimisation
- Piezoelectric

### ASJC Scopus subject areas

- Materials Science(all)
- Mechanical Engineering

### Cite this

*Journal of Intelligent Material Systems and Structures*,

*26*(11), 1442-1451. https://doi.org/10.1177/1045389X14546648

**An enhanced physics-based model to estimate the displacement of piezoelectric actuators.** / Miri, Narges; Mohammadzaheri, Morteza; Chen, Lei.

Research output: Contribution to journal › Article

*Journal of Intelligent Material Systems and Structures*, vol. 26, no. 11, pp. 1442-1451. https://doi.org/10.1177/1045389X14546648

}

TY - JOUR

T1 - An enhanced physics-based model to estimate the displacement of piezoelectric actuators

AU - Miri, Narges

AU - Mohammadzaheri, Morteza

AU - Chen, Lei

PY - 2015/7/3

Y1 - 2015/7/3

N2 - Piezoelectric actuators are the foremost actuators in the area of nanopositioning. However, the sensors employed to measure the actuator displacement are expensive and difficult, if not impossible, to use. Mathematical models can map the easy-to-measure electrical signals to the displacements of the actuators as the displacement sensors are replaced with the models. In addition, these models can be used in model-based control system design. Two main groups of mathematical models are used for this purpose: black box and physics-based models. As an advantage, the latter has a much smaller number of parameters reducing computational demand in real-time applications. However, physics-based models suffer from (1) the relatively low accuracy of the models and (2) non-standard and ad-hoc parameter identification methods. In this research, to improve the model accuracy, mathematical structure of a well-known physics-based model, the Voigt model, is enhanced by adding two complementary terms inspired by another model, the Preisach model. Then, a standard method based on the evolutionary algorithms is proposed to identify the model's parameters. The proposed ideas are substantiated to increase the applicability and accuracy of the model, and they are easily extendable to other physics-based models of piezoelectric actuators. The newly proposed enhanced structure of the Voigt model doubles the estimation accuracy of the original model and results in accuracies comparable with black box models.

AB - Piezoelectric actuators are the foremost actuators in the area of nanopositioning. However, the sensors employed to measure the actuator displacement are expensive and difficult, if not impossible, to use. Mathematical models can map the easy-to-measure electrical signals to the displacements of the actuators as the displacement sensors are replaced with the models. In addition, these models can be used in model-based control system design. Two main groups of mathematical models are used for this purpose: black box and physics-based models. As an advantage, the latter has a much smaller number of parameters reducing computational demand in real-time applications. However, physics-based models suffer from (1) the relatively low accuracy of the models and (2) non-standard and ad-hoc parameter identification methods. In this research, to improve the model accuracy, mathematical structure of a well-known physics-based model, the Voigt model, is enhanced by adding two complementary terms inspired by another model, the Preisach model. Then, a standard method based on the evolutionary algorithms is proposed to identify the model's parameters. The proposed ideas are substantiated to increase the applicability and accuracy of the model, and they are easily extendable to other physics-based models of piezoelectric actuators. The newly proposed enhanced structure of the Voigt model doubles the estimation accuracy of the original model and results in accuracies comparable with black box models.

KW - actuator

KW - control

KW - optimisation

KW - Piezoelectric

UR - http://www.scopus.com/inward/record.url?scp=84935146440&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84935146440&partnerID=8YFLogxK

U2 - 10.1177/1045389X14546648

DO - 10.1177/1045389X14546648

M3 - Article

AN - SCOPUS:84935146440

VL - 26

SP - 1442

EP - 1451

JO - Journal of Intelligent Material Systems and Structures

JF - Journal of Intelligent Material Systems and Structures

SN - 1045-389X

IS - 11

ER -