Interval Methods for Model Qualification: Methodology and Advanced Application

It is often too complex to use, and sometimes impossible to obtain, an actual model in simulation or command eld . To handle a system in practice, a simpli cation of the real model is then necessary. This simpli cation 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 quali es the simpli cation 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.Our approach is experimentally validated on a robotic application. Key-words: Modelling, Simpli cation, Interval analysis, Cable-driven Robot ∗ Inria † Inria,I3S ‡ Inria ha l-0 06 68 95 0, v er si on 1 10 F eb 2 01 2 Méthodes intervalles pour la quali cation de modèles simpli és rapport de recherche Inria Résumé : Ce document presente une methode base sur l'analyse par intervalle servant a la veri cation d'une hypothese utilisee dans le cadre d'une simpli cation de modele. Une application en robotique est presentee. Mots-clés : Modèlisation, Simpli cation, Analyse par intervalles, Robot à câbles ha l-0 06 68 95 0, v er si on 1 10 F eb 2 01 2 Interval Methods for Model Quali cation: Methodology and Advanced Application3