On a Robust Modeling of Piezo-Systems

Corbier, Christophe; Boukari, Abdou Fadel; Carmona, Jean-Claude; Martinez, Victor Manuel Alvarado; Moraru, George; Malburet, François

doi:10.1115/1.4005499

Cited by 6 publications

(1 citation statement)

References 33 publications

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“…For more detail, see [13]. In a previous study (see [32]) on the piezo-systems, we show that small values of k in OE0:05; 2 lead to derive relevant Output Error models. In this study, even though the prediction errors are strongly disturbed by numerous outliers leading to a pdf with heavy tail, the choice of the small values of k near 0.05 allows to obtain interesting results.…”

Section: Choice Of the Tuning Constant To Reduce The Influence Of Thesupporting

confidence: 53%

Extension of the tuning constant in the Huber's function for robust modeling of piezoelectric systems

Corbier

Carmona

2014

Adaptive Control & Signal

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This paper proposes a new modeling approach that is experimentally validated on piezoelectric systems in order to provide a black-box pseudolinear model for complex systems control. Most of the time, one uses physical based approaches. However, sometimes complex phenomena occur in the system due to atypical changes of the process behavior, output noise or some hard nonlinearities. Therefore, we adopt identification methods to achieve the modeling task. The microdisplacements of the piezoelectric systems generate atypical data named outliers, leading to large estimated prediction errors. Since these errors disturb the classical normal probability density function, we choose here, as corrupted distribution model, the gross error model (GEM). In order to deal more efficiently with the outliers, we use the Huber's function, as mixed L 2 =L 1 norms in which the tuning threshold named scaling factor is extended. From this function, a cost function also named PREC as parameterized robust estimation criterion is established. The identification is performed by choosing an Output Error model structure. In order to express the asymptotic covariance matrix of the robust estimator, we present a L finite Taylor's expansion to linearize the gradient and the hessian of the PREC. Experimental results are presented and discussed.

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Section: Choice Of the Tuning Constant To Reduce The Influence Of Thesupporting

confidence: 53%

Extension of the tuning constant in the Huber's function for robust modeling of piezoelectric systems

Corbier

Carmona

2014

Adaptive Control & Signal

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Robust Black-Box Modeling of Piezoelectric Actuators for Vibration Drilling Control

Corbier

Carmona

2014

J Intell Robot Syst

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Outliers detection method of multiple measuring points of parameters in power plant units

Chen

2015

Applied Thermal Engineering

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On a Robust Modeling of Piezo-Systems

Abstract: is an open access repository that collects the work of Arts et Métiers ParisTech researchers and makes it freely available over the web where possible.

Cited by 6 publications

References 33 publications

Extension of the tuning constant in the Huber's function for robust modeling of piezoelectric systems

Extension of the tuning constant in the Huber's function for robust modeling of piezoelectric systems

Robust Black-Box Modeling of Piezoelectric Actuators for Vibration Drilling Control

Outliers detection method of multiple measuring points of parameters in power plant units

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