A comparative study on the use of black box modelling for piezoelectric actuators

Mohammadzaheri, Morteza; Grainger, Sally; Bazghaleh, Mohsen

doi:10.1007/s00170-012-3987-5

Cited by 24 publications

(17 citation statements)

References 55 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…represents the Preisach density function (Mohammadzaheri, 2011, Robert et al, 2001. Regarding the input voltage behaviour (ascending/descending voltage), Equation (3) is converted to: Ascending…”

Section: Preisach Modelmentioning

confidence: 99%

“…In this paper, available recorded experimental input-output (piezoelectric voltage-piezoelectric displacement) data are used to identify the model parameters (Mohammadzaheri et al, 2012b). The model error is defined as the average of absolute discrepancy for the model output and the real output:…”

Section: Parameter Identificationmentioning

confidence: 99%

“…Step Prediction' (OSP) error (Mohammadzaheri et al, 2012a). In the second approach to calculate the model error, after the first estimation, previously estimated value(s) of the system output(s) are used as model input(s) (instead of the measured values).…”

Section: Modelling Error Approachesmentioning

confidence: 99%

“…In the second approach to calculate the model error, after the first estimation, previously estimated value(s) of the system output(s) are used as model input(s) (instead of the measured values). The model error in this approach is called 'Simulation' error (Mohammadzaheri et al, 2012a). In dynamic systems, the current value of the system output(s) depends on its (their) previous value(s).…”

Section: Modelling Error Approachesmentioning

confidence: 99%

“…The models estimate the displacement of piezoelectric actuators using the voltage across the actuators. Different types of mathematical models have been employed for the modelling purpose such as black box models designed through system-identification techniques (Mohammadzaheri et al, 2012a, Mohammadzaheri et al, 2012c. Moreover, a few physics-based models, inspired by physical phenomena, have been introduced to estimate the displacement of piezoelectric actuators.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

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

Miri

Mohammadzaheri

Chen

2014

Journal of Intelligent Material Systems and Structures

Self Cite

View full text Add to dashboard Cite

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.

show abstract

Section: Preisach Modelmentioning

confidence: 99%

Section: Parameter Identificationmentioning

confidence: 99%

Section: Modelling Error Approachesmentioning

confidence: 99%

Section: Modelling Error Approachesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations