On the stability analysis of a class of multiple models

Abstract This paper proposes a method to discuss the stability analysis of multiple models. The proposed stability analysis is based on the use of scalar Lyapunov functions and the properties of M-matrices. An example is included to illustrate the proposed method

Espace de parité pour les systèmes linéaires incertains. Synthèse, quelques résultats nouveaux et mise en oeuvre

Pour analyser le bon fonctionnement d'un système, l'une des techniques couramment utilisées consiste à tester la nullité d'équations de redondance entre différentes grandeurs connues caractérisant ce système. Ces équations sont généralement obtenues en éliminant, des équations modélisant le système, les grandeurs inconnues ; dans le cas où les paramètres de ce modèle sont incertains, le résultat de l'élimination est critiquable. Dans cette communication, on expose ce problème ainsi qu'une technique de génération d'équations de redondance robustes vis-à-vis des imprécisions des paramètres. Des exemples illustrent les différentes propositions

Fault diagnosis for nonlinear systems represented by heterogeneous multiple models

Abstract-This paper proposes two observer-based FDI strategies for nonlinear systems represented by a particular class of multiple model using heterogeneous submodels. The structure of this interesting multiple model is firstly presented in order to design two kinds of state observers. The first observer, known as proportional observer (PO), is an extension of the classic Luenberger observer, in this way, it can be used to obtain an estimation of the system state. The second proposed observer, known as proportional-integral observer (PIO), makes it possible the simultaneous state and unknown input (e.g. a fault) estimation of the system under investigation. The convergence towards zero of the estimation errors provided by these observers is investigated with the help of the Lyapunov method. The P observer as well as the PI observer are employed in a FDI strategy in order to accomplish the detection, the localisation and eventually the estimation of sensor faults acting on the system. These two strategies are finally validated in simulation by considering a simplified model of a bioreactor

State constrained tracking control for nonlinear systems

Abstract This work addresses the model reference tracking control problem. It aims to highlight the encountered difficulties and the proposed solutions to achieve the tracking objective. Based on a literature overview of linear and nonlinear reference tracking, the achievements and the limitations of the existing strategies are highlighted. This motivates the present work to propose clear control algorithms for perfect and approximate tracking controls of nonlinear systems described by Takagi-Sugeno models. First, perfect nonlinear tracking control is addressed and necessary structural conditions are stated. If these conditions do not hold, approximate tracking control is proposed and the choice of the reference model to be tracked as well as the choice of the criterion to be minimized are discussed with respect to the desired objectives. The case of constrained control input is also considered in order to anticipate and counteract the effect of the control saturation

Damage detection and localization in pipeline using sparse estimation of ultrasonic guided waves signals

International audienceThis paper focuses on the development of a method for damage detection and localization in pipeline structures. These structures are subject to variation of environmental and operational conditions (EOCs) which will have an impact on the collected signals. Since damage detection is generally based on comparison between the reference signals and the current signals acquired from the structure, the effects of EOCs will give rise to false alarm. This issue is addressed by selecting from the database of reference signals those with similar or very close EOCs. Such an operation can be performed by calculating the sparse estimation of the current signal. The estimation error is used as an indication of the presence of damage. Actually, a damage signal will be characterized by a high estimation error compared to that of a healthy signal. The position of the detected damage is obtained by calculating the estimation error on a sliding window over the damaged signal. This method was tested on signals collected on a small scale pipeline placed in laboratory conditions. Results have shown that the created damage was successfully detected and localized

Analyse d'un système de mesure à paramètres incertains

- Pour analyser le bon fonctionnement d'un système de mesure, l'une des techniques couramment utilisées consiste à tester la nullité d'équations de redondance entre différentes grandeurs connues caractérisant ce système. Dans ce qui suit, on insiste sur la conception du vecteur parité qui est à la base de nombreuses analyses de diagnostic utilisant un modèle. Lorsque le modèle est connu avec une certaine imprécision, le vecteur parité est lui aussi sensible à cette imprécision ; il semble utile d'en étudier l'influence. On examine donc le cas de systèmes de mesures dont les paramètres sont incertains mais bornés. L'objectif est de construire l'enveloppe du vecteur parité prenant en compte les incertitudes paramétriques

Observabilite, diagnostic et validation de donnees des procedes industriels

SIGLECNRS T 62139 / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc