josé RAGOT

This paper presents a method for state-estimation of Takagi-Sugeno descriptor systems (TSDS) affected by unknown inputs (UI). For ease of implementation's sake, the proposed observers are not in descriptor form but in usual form. Sufficient existence conditions of the unknown input observers are given and strict linear matrix inequalities (LMI) are solved to determine the gain of the observers. If the perfect unknown input decoupling is not possible, the UI observer is designed in order to minimise the L2-gain from the UI to the state estimation error. The two previous objectives can be mixed in order to decouple the estimation to a subset of the UI, while attenuating the L2 gain from the other UI to the estimation. The proposed UI observers are used for robust fault diagnosis. Fault diagnosis for TSDS is performed by designing a bank of observers. A simple decision logic and thresholds setting allow to determine the occurring fault. The results are established for both the continuous and the discrete time cases. The proposed method is illustrated by a numerical example.

Dans cet article, nous proposons une nouvelle approche formelle pour l'évaluation des bornes de l'état d'un système incertain. La méthode qui en résulte utilise une représentation par intervalles, et repose sur la construction d'un système dynamique augmenté, où le nouveau vecteur d'état est composé des bornes inférieure et supérieure de l'état du système incertain. Il est important de noter que nous considérons des incertitudes structurées, où seules les bornes de chaque coefficient des matrices du système sont supposées ...

Un des aspect important du contrôle industriel est l'obtention et la visualisation d'informations pertinentes qui donnent une image des conditions opératoires d'un procédé. De façon classique maintenant, la théorie de l'estimation d'état fournit des algorithmes bien adaptés à cet objectif. Cependant, ces algorithmes sont difficiles de mise en oeuvre en raison des dimensions importantes des procédés. Cette communication présente des techniques faisant appel à différentes décompositions: décomposition par l'observabilité ...

L'estimation est l'un des concepts les plus utilis{\'e}s en automatique, dans les domaines de l'identification, de l'observation, de la commande et du diagnostic. Le cas des syst{\`e}mes lin{\'e}aires {\`a} param{\`e}tres constants est bien r{\'e}solu ainsi que l'extension aux syst{\`e}mes {\`a} param{\`e}tres variables. Lorsque les syst{\`e}mes sont affect{\'e}s de perturbations non mesur{\'e}es, la probl{\'e}matique est plus d{\'e}licate et les approches {\`a}

Dans cette communication, nous proposons une m{\'e}thode d'estimation d'{\'e}tat d'un syst{\`e}me non lin{\'e}aire repr{\'e}sent{\'e} par un multi-mod{\`e}le de type Takagi--Sugeno dont les fonctions d'activation d{\'e}pendent de l'{\'e}tat. Pour cela, nous proposons la synth{\`e}se d'un multi-observateur de Luenberger et nous montrons comment d{\'e}terminer les gains du multi-observateur pour garantir la convergence globale asymptotique vers z{\'e}ro de l'erreur d'estimation d'{\'e}tat. Les conditions

Résumé/Abstract Ce travail s' inscrit dans le cadre général du contrôle de la qualité de l'eau. Plus particulièrement, il est consacré à la mesure en continu, sans prélèvement ni additif, de la teneur en cuivre dans les eaux usées. La solution proposée est une adaptation de la potentiométrie sélective à l'aide d'électrode spécifique (Ion Selective Electrode: ISE) aux milieux non contrôlés. Un banc expérimental, reproduisant les conditions observées dans les eaux de rejet, a permis de quantifier le degré de dépendance de la réponse de l'ISE ...

Abstract This paper deals with the synthesis of optimality conditions for the truncated network of the generalized orthonormal basis in the case where all the poles belong to the set of real numbers. These conditions are brought to a very simple form, but their solutions are not trivial. They generalize the optimality conditions for the truncated Laguerre network and are very attractive in system identification, model representation, and model reduction frameworks

Abstract This communication deals with the problem of designing a non-linear observer for fault detection and localisation for a wide class of non-linear systems subjected to bounded non-linearities. A dedicated non-linear observer schema (DNOS) for fault detection and identification in reconstructible systems is proposed

Abstract In this paper, modelling of MIMO nonlinear dynamic systems using a Takagi-Sugeno structure (1985) is discussed. A new formulation which leads to another interpretation of Takagi-Sugeno model and an improvement of the model parameter estimation is proposed. From inputs and outputs data, an identification algorithm of this model is presented. The parameter estimation is based on computation of sensitivity functions of the model with respect to parameters

The study deals with the design and construction of a particle size analyzer that can measure the size of particles belonging to a monophasic pulp. A curve related to particle size analysis can be obtained by interpretation of a density measurement. The working principle of the analyzer is based on the settling velocity of particles. The numerical treatments needed for

Principal component analysis (PCA) has been applied successfully for data compression. Here, the purpose is to use PCA for detection and isolation of faults afiecting measurements by using both reconstruction and projection of variables. Then, this procedure for outliers detection and isolation is successfully applied to an example with multiple faults. Mots clefs : statistique de processus, analyse de donnees

ABSTRACT In this paper, we present the synthesis of a robust controller for uncertain discrete systems. The synthesis method of such a robust controller is the generalization of the Loop Shaping Design Procedure (LSDP) approach of McFarlane and Glover in the discrete case based on the work of Gu et al. We exploit the bilinear transform known as Tustin’s method in order to formulate the discrete loop shaping technique. A discrete weighting filter and a shaped discrete plant result from this technique. By taking into account the coprime factor uncertainty representation for the resulting shaped plant and by applying the small gain theorem, we define the concept of the robust stabilization of the discrete LSDP approach. This concept is based on the resolution of an optimization problem characterized by the maximum stability margin for the synthesis of the robust controller. To calculate the robust controller we transform this problem to a standard robust controller design based on the resolution of the Riccati equations. Also, we present the gap metric theory to characterize the controller’s robustness. We note that the resulting final controller is the combination of the discrete weighting filter and the robust controller. We propose then to exploit the recent work of Bouzrara et al. in order to develop a reduced robust controller by expanding the final controller on two independent Laguerre orthonormal bases. The discrete LSDP and the reduced controller approaches were validated on a Continuous Stirred Tank Reactor chemical reactor for a set of different equilibrium points in order to take into account the nonlinearities.

Abstract The design of a scheduled observer which allows us to estimate the state of an affine LPV (linear parameter varying) system is investigated. The state and the gain matrices of the observer are scheduled by using an interpolation method which is linear according to each parameter but which is nonlinear according to the parameter vector. The stability of the estimation error is based on the existence of an affine parameter-dependent Lyapunov function. The problem of the observer design and the existence of a such Lyapunov ...

The aim is to identify the parameter values of a given input-output model such that estimated model outputs are consistent with measured outputs of the system to be modeled. Parameter estimation based on a set-membership approach is a non-probabilistic method for characterizing the uncertainty with which each model parameter is known. In this case, the sought model is consistent with

ABSTRACT This paper presents a new scheme for sensor fault tolerant control for nonlinear systems based on the Takagi–Sugeno modeling. First, a structured residual generator aimed at detecting and isolating sensor faults is designed. A bank of observers controlled either by only one system output or a set of outputs is then implemented, leading to a set of state estimates. The parallel distributed compensation structure is adopted to design the fault tolerant controller. The novelty in this paper is that the estimated state used in the controller is a weighted state vector obtained from all the estimated states provided by the different observers. The weighting functions depend on the residual vector signals delivered by the residual generator. They are designed to avoid crisp switches in the control law. Indeed, the interesting feature of the proposed approach is to avoid the commonly used switching strategy. For each residual component, the greater its magnitude is, the less the weight affected to the corresponding state estimate is. Consequently, the controller only uses estimations computed on the basis of healthy measurements. The closed-loop stability is studied with the Lyapunov theory, and the obtained conditions are expressed as a set of linear matrix inequalities. The proposed residual generation and fault tolerant controller are applied to a vehicle lateral dynamics affected by sensor faults. Copyright

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Abstract We present a review of the pattern recognition approach in order to study its ability to solve the diagnosis problem of technological systems. We first state the problem and highlight the link between pattern recognition and diagnosis. Many theoretical and practical factors need to be considered. We then describe a common adaptive diagnosis procedure with emphasis on the design and real time operation. Finally, we conclude with directions for future work to solve this problem

Il s'agit d'{\'e}tudier une ou plusieurs m{\'e}thodes de classification de donn{\'e}es dans le but de d{\'e}finir un syst{\`e}me de diagnostic ou de surveillance g{\'e}n{\'e}rique d'un parc de machines ou plus g{\'e}n{\'e}ralement de syst{\`e}mes. Dans le cas consid{\'e}r{\'e}, les donn{\'e}es expertis{\'e}es viennent de plusieurs {\'e}l{\'e}ments du parc. Elles constituent l'ensemble d'apprentissage de d{\'e}part. L'approche consiste {\`a} d{\'e}finir un classifieur par {\'e}l{\'e}ment