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The aim of this thesis is to design a nonlinear observer as a diagnostic tool for continuous-time nonlinear systems with discrete-time measurements. We begin with the study of some observability notions concerning the considered nonlinear systems, following by the presents of three typical optimization-based nonlinear observers and observer-based diagnostic methods. Inspired by the existing approaches, a finite memory observer is then designed for a class of nonlinear systems in the presence of both process and measurement noises in order to perform fault detection and isolation of sensor and actuator faults. In the second part, a nonlinear observer based on augmented model is then designed to simultaneously estimate both system states and unknown inputs. The robustness with respect to the diverse noises is studied, as well as the study of the minimum amplitude of fault for the detection. The EWMA algorithm was also introduced and analyzed for its performance in detection. Multiple simultaneous faults are also detected and identified in this part. At the end of this thesis, a finite memory observer is designed for the nonlinear time-varying systems on the basis of the fundamental synthesis for linear time-varying systems., L’objectif de cette thèse est de développer un observateur non linéaire pour un outil de diagnostic pour des systèmes non linéaires à temps continu et à mesures discrètes. Ce mémoire débute par l’étude de notions d’observabilité faisant le point sur l’observation de ces systèmes. Nous enchaînons ensuite par l’analyse d’observateurs non linéaires obtenu par optimisation, puis nous présentons les méthodes de diagnostic à l'aide d'observateurs. Un observateur à mémoire finie est ensuite synthétisé pour détecter et localiser les défauts capteurs et actionneurs d’une classe de systèmes non linéaires en présence à la fois de bruit de processus et de bruit de mesures. De plus, un observateur non linéaire est également construit sur un modèle augmenté pour estimer simultanément les états du système et les entrées inconnues. Une étude de robustesse vis à vis des divers bruits a été menée, ainsi que l'étude de la définition des défaut d'amplitude minimale pour la détection. L'utilisation de l'algorithme EWMA a également été introduit pour ses performance en détection. Multiple défauts simultanés ont été détectés et identifiés dans cette partie. À la fin de cette thèse, un observateur à mémoire finie est développé pour les systèmes non linéaires à temps variants.

This paper focuses on a tool to estimate lost data on network control systems. The tool is also able to detect loss of data integrity and estimate the correct value. A new formulation of the Finite Memory Observer using a finite collection of measurements and input is proposed to achieve these goals. First, the realisation of this tool is based on a Markov chain used to implement an event triggering mechanism applied to models of lost network measurement packets. The Finite Memory Observer (FMO) is based on a continuous time system model which corresponds better to time management in further works. The new formulation, dealing with loss of measurement packets, uses timestamping of data received to adjust the data estimation-predictions generated. The propagation of data loss in the observer's window and its effect on the estimate is presented. Finally, on a simple packet loss scenario, the accuracy of this prediction-estimation observer is presented. Secondly, the FMO is used to detect modification of data. Given the packet strategy, when a data modification is detected , the associated measurement will be not used for its estimation/prediction.

The works described in this thesis deal with the integrity and availability of networked control systems information. The importance of this has been highlighted by the growing number of cyber-attacks. A finite memory observer is proposed as a tool to answer this problem. This tool provides an answer to the problems of packet loss on the network as well as to static and dynamic cyber-attacks using bias injection. Combined with a detection-decision-correction strategy, the reliability of system information during cyber-attacks is ensured. The uncertainties of the models of some systems are also taken into account in the development of the finite memory observer. More specifically, two categories of uncertainties are addressed (uncertain systems and correlated noise systems). All case studies are illustrated by numerical simulations confirming the qualities of this tool. Finally, we will apply this tool to teleoperated systems subjected to new types of attacks called “smart attacks”.; Les travaux décrits dans cette thèse concernent l’intégrité et la disponibilité des informations de systèmes commandés en réseau. L’importance de celles-ci a été mise en exergue face au nombre de plus en plus important de cyber-attaques. Nous proposons comme outil pour répondre à cette problématique un observateur à mémoire finie. Cet outil apporte une réponse aux problèmes de pertes de paquets sur le réseau ainsi qu’aux cyber-attaques statiques et dynamiques par injection de biais. Associé à une stratégie de détection-décision-correction, la fiabilité des informations de systèmes lors de cyber-attaques est assurée. Les incertitudes du modèle pour certains systèmes sont également prises en compte dans le développement de l’observateur à mémoire finie. Plus particulièrement, deux catégories d’incertitudes sont traitées (systèmes incertains et systèmes à bruits corrélés). Tous les cas d’études sont illustrés par des simulations numériques confirmant les qualités de cet outil. Enfin, nous appliquerons cet outil aux systèmes télé-opérés soumis à de nouveaux types d’attaques appelés attaques intelligentes".

The works described in this thesis deal with the integrity and availability of networked control systems information. The importance of this has been highlighted by the growing number of cyber-attacks. A finite memory observer is proposed as a tool to answer this problem. This tool provides an answer to the problems of packet loss on the network as well as to static and dynamic cyber-attacks using bias injection. Combined with a detection-decision-correction strategy, the reliability of system information during cyber-attacks is ensured. The uncertainties of the models of some systems are also taken into account in the development of the finite memory observer. More specifically, two categories of uncertainties are addressed (uncertain systems and correlated noise systems). All case studies are illustrated by numerical simulations confirming the qualities of this tool. Finally, we will apply this tool to teleoperated systems subjected to new types of attacks called “smart attacks”., Les travaux décrits dans cette thèse concernent l’intégrité et la disponibilité des informations de systèmes commandés en réseau. L’importance de celles-ci a été mise en exergue face au nombre de plus en plus important de cyber-attaques. Nous proposons comme outil pour répondre à cette problématique un observateur à mémoire finie. Cet outil apporte une réponse aux problèmes de pertes de paquets sur le réseau ainsi qu’aux cyber-attaques statiques et dynamiques par injection de biais. Associé à une stratégie de détection-décision-correction, la fiabilité des informations de systèmes lors de cyber-attaques est assurée. Les incertitudes du modèle pour certains systèmes sont également prises en compte dans le développement de l’observateur à mémoire finie. Plus particulièrement, deux catégories d’incertitudes sont traitées (systèmes incertains et systèmes à bruits corrélés). Tous les cas d’études sont illustrés par des simulations numériques confirmant les qualités de cet outil. Enfin, nous appliquerons cet outil aux systèmes télé-opérés soumis à de nouveaux types d’attaques appelés attaques intelligentes".

International audience; This paper presents the development of a Finite Memory Observer in systems with a correlation between measurement and state noises. This work proves the interest of designing observer statements adapted to systems with correlated noises. It also develops a theoretical form of continuous time representation of Finite Memory Observers. The estimators obtained are studied in different noise behaviors cases and with different window length values. These studies show the robustness of the observer even in presence of unknown noises. Finally, this estimator is applied to the diagnostic of a faulty system with correlated measurement and state noises.

International audience; In this paper, we develop a fault detection method for switching dynamic systems with unknown inputs. These systems are represented by several linear models, each of them being associated to a particular operation mode. The proposed method is based on the use of Finite Memory Observers and mode probabilities with the aim to finding the operating mode of the system and estimating the unknown input. The resulting method also uses the knowledge of a priori information on the mode transition probabilities represented by a Markov chain. The proposed algorithm belongs to the class of the supervised algorithms where the fault to be detected are a priori indexed and modelled. First, the method is used for fault detection in the case of a linear system characterized by a normal model of operation and several fault models. Then, it applies for fault detection in the case of a linear system with unknown input where state and unknown input estimation are done simultaneously. A comparison with the Generalized Pseudo- Bayesian method is carry out showing the advantages of the suggested method.

International audience; In the past decade, interest has been focused on the use of analytic redundancy for the Fault Detection and Isolation (FDI) (Frank, 1990; Gertler, 1991). Many applications in the FDI area use the state estimation technique to generate the accentuated fault functions, so-called residuals. Subsequent analysis of residuals may provide an information about a faulty component localisation. It is well known that infinite observer memory leads to the so-called divergence phenomenon caused by the model errors that observer tends to accumulate during its performance [Toda et al., 1978]. Moreover, the infinite memory inflicts observer insensitivity to recent measurements. This shortcoming brings us to the conclusion that an observer structure with finite memory would be more appropriate for the FDI. This paper presents extensions and improvements on the finite memory observer. The main contribution is to incorporate the parity relation design and observer into a diagnosis scheme and how to choose optimal length of the memory. The application of the finite memory observer to the sensor fault detection problem is illustrated by a numerical example. Simulation results show that the method is very effective for robust fault detection.

International audience; In this paper, we propose two methods to detect and localize instrument or actuator failures in linear dynamic systems. These methods are based on analytical redundancy and use a simultaneous states and inputs estimation. Using the concept of standardized least square residuals, residuals can be generated in a umber of ways and the design of fault detection and fault isolation scheme can be presented. The performances of the proposed methods are illustrated on a real process: an inverted pendulum.