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Reports (Research Report) Year : 2012

Interval Methods for Model Qualification: Methodology and Advanced Application

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Abstract

It is often too complex to use, and sometimes impossible to obtain, an actual model in simulation or command field . To handle a system in practice, a simplification of the real model is then necessary. This simplification goes through some hypotheses made on the system or the modeling approach. In this paper, we deal with all models that can be expressed by real-valued variables involved in analytical relations and depending on parameters. We propose a method that qualifies the simplification validity by verifying a quality threshold on the hypothesis relevance. This method, based on interval analysis, can check the acceptance of the hypothesis in a full range of the whole model space, and can give bounds to the quality threshold and to the model parameters.% to keep the simplified model acceptable. Our approach is experimentally validated on a robotic application.
Ce document présente une méthode base sur l'analyse par intervalle servant a la vérification d'une hypothèse utilisée dans le cadre d'une simplification de modèle. Une application en robotique est présentée.
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Dates and versions

hal-00668950 , version 1 (10-02-2012)

Identifiers

  • HAL Id : hal-00668950 , version 1

Cite

Julien Alexandre Dit Sandretto, Gilles Trombettoni, David Daney. Interval Methods for Model Qualification: Methodology and Advanced Application. [Research Report] RR-7880, INRIA. 2012, pp.23. ⟨hal-00668950⟩
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