<p>This thesis considers the problem of fault diagnosis and fault-tolerant control (FTC) for chemical process systems with nonlinear dynamics. The primary objective of fault diagnosis discussed in this work is to identify the failed actuator or sensor by using the information embodied in a process model, as well as input and output data. To this end, an active fault isolation method is first proposed to identify actuator faults and process disturbances by utilizing control action and process nonlinearity. The key idea is to move the process to a region upon fault detection where the effect of each fault can be differentiated from others. The proposed method enables isolation of faults that may not be achievable under nominal operation. This work then investigates the problem of sensor fault isolation by exploiting model-based sensor redundancy through state observer design. Specifically, a high-gain observer is presented and the stability property of the closed-loop system is rigorously established. A method that uses a bank of high-gain observers is then proposed to isolate sensor faults, which explicitly accounts for process nonlinearity, and to continue nominal operation upon fault isolation. In addition to fault diagnosis, this work addresses the problem of handling severe actuator faults using a safe-parking approach and integrating fault diagnosis and safe-parking techniques in a unified fault-handling framework. In particular, several practical issues are considered for the design and implementation of safe-parking techniques, including changes in process dynamics, the network structure of a chemical plant, and actuators frozen at arbitrary positions. The advantage of this approach is that it enables stable process operation under faulty conditions, avoiding the partial or entire shutdown of a chemical plant and resulting economic losses. The efficacy of the proposed fault diagnosis and FTC methods is demonstrated through numerous simulations of chemical process examples.</p> / Doctor of Philosophy (PhD)

Cette thèse est une contribution au problème du pronostic des systèmes complexes. Plus précisément, elle concerne l'approche basée modèles et est composée de trois contributions principales. Tout d'abord, dans une première contribution une définition du concept de pronostic est proposée et est positionnée par rapport aux concepts de diagnostic et de diagnostic prédictif. Pour cela, une notion de contrainte temporelle a été introduite afin de donner toute pertinence à la prédiction réalisée. Il a également été montré comment le pronostic est lié à la notion d'accessibilité en temps fini.La deuxième contribution est dédiée à l'utilisation des observateurs à convergence en temps fini pour la problématique du pronostic. Une méthodologie de pronostic est présentée pour les systèmes non linéaires à échelle de temps multiple. Puis, une troisième contribution est introduite par l'utilisation des observateurs par intervalle pour le pronostic. Une méthodologie de pronostic est proposée pour les systèmes non linéaires incertains à échelle de temps multiple. Pour illustrer les différents résultats théoriques, des simulations ont été conduites sur un modèle de comportement d'un oscillateur électromécanique. / This thesis is a contribution to the problem of a complex system prognosis. More precisely, it concerns the model-based prognosis approach and the thesis is divided into three main contributions. First of all, a definition of prognosis concept is proposed as a first contribution and is positionned in reference to the diagnosis and predictive diagnosis concepts. For that, a notion of temporal constraint is introduced to give all pertinence to the prediction achieved. It is also shown how prognosis is linked to the finite time reachability notion. The second contribution is dedicated to the use of finite time convergence observer for the prognosis problem. A prognosis methodology is presented for nonlinear multiple time scale systems. Then, a last contribution is introduced through the use of interval observer for the prognosis problem. A pronognosis methodology is proposed for nonlinear uncertain multiple time scale systems. To illustrate the theorical results, simulations are achieved based on a model of an electromechanical oscillator system.

The main body of this thesis consists of six appended papers. In the  first two, different  cooperative surveillance problems are considered. The second two consider different aspects of the trajectory planning problem, while the last two deal with observer design for mobile robotic and Euler-Lagrange systems respectively.In Papers A and B,  a combinatorial optimization based framework to cooperative surveillance missions using multiple Unmanned Ground Vehicles (UGVs) is proposed. In particular, Paper A  considers the the Minimum Time UGV Surveillance Problem (MTUSP) while Paper B treats the Connectivity Constrained UGV Surveillance Problem (CUSP). The minimum time formulation is the following. Given a set of surveillance UGVs and a polyhedral area, find waypoint-paths for all UGVs such that every point of the area is visible from  a point on a waypoint-path and such that the time for executing the search in parallel is minimized.  The connectivity constrained formulation  extends the MTUSP by additionally requiring the induced information graph to be  kept recurrently connected  at the time instants when the UGVs  perform the surveillance mission.  In these two papers, the NP-hardness of  both these problems are shown and decomposition techniques are proposed that allow us to find an approximative solution efficiently in an algorithmic manner.Paper C addresses the problem of designing a real time, high performance trajectory planner for an aerial vehicle that uses information about terrain and enemy threats, to fly low and avoid radar exposure on the way to a given target. The high-level framework augments Receding Horizon Control (RHC) with a graph based terminal cost that captures the global characteristics of the environment.  An important issue with RHC is to make sure that the greedy, short term optimization does not lead to long term problems, which in our case boils down to two things: not getting into situations where a collision is unavoidable, and making sure that the destination is actually reached. Hence, the main contribution of this paper is to present a trajectory planner with provable safety and task completion properties. Direct methods for trajectory optimization are traditionally based on a priori temporal discretization and collocation methods. In Paper D, the problem of adaptive node distribution is formulated as a constrained optimization problem, which is to be included in the underlying nonlinear mathematical programming problem. The benefits of utilizing the suggested method for  online  trajectory optimization are illustrated by a missile guidance example.In Paper E, the problem of active observer design for an important class of non-uniformly observable systems, namely mobile robotic systems, is considered. The set of feasible configurations and the set of output flow equivalent states are defined. It is shown that the inter-relation between these two sets may serve as the basis for design of active observers. The proposed observer design methodology is illustrated by considering a  unicycle robot model, equipped with a set of range-measuring sensors. Finally, in Paper F, a geometrically intrinsic observer for Euler-Lagrange systems is defined and analyzed. This observer is a generalization of the observer proposed by Aghannan and Rouchon. Their contractivity result is reproduced and complemented  by  a proof  that the region of contraction is infinitely thin. Moreover, assuming a priori bounds on the velocities, convergence of the observer is shown by means of Lyapunov's direct method in the case of configuration manifolds with constant curvature. / QC 20100622 / TAIS, AURES

<p>The main body of this thesis consists of four appended papers. The first two consider different aspects of the trajectory planning problem, while the last two deal with observer design for mobile robotic and Euler-Lagrange systems respectively.</p><p>The first paper addresses the problem of designing a real time, high performance trajectory planner for aerial vehicles. The main contribution is two-fold. Firstly, by augmenting a novel safety maneuver at the end of the planned trajectory, this paper extends previous results by having provable safety properties in a 3D setting. Secondly, assuming initial feasibility, the planning method is shown to have finite time task completion. Moreover, in the second part of the paper, the problem of simultaneous arrival of multiple aerial vehicles is considered. By using a time-scale separation principle, one is able to adopt standard Laplacian control to this consensus problem, which is neither unconstrained, nor first order.</p><p>Direct methods for trajectory optimization are traditionally based on<i> a</i> <i>priori </i>temporal discretization and collocation methods. In the second paper, the problem of adaptive node distribution is formulated as a constrained optimization problem, which is to be included in the underlying nonlinear mathematical programming problem. The benefits of utilizing the suggested method for online trajectory optimization are illustrated by a missile guidance example.</p><p>In the third paper, the problem of active observer design for an important class of non-uniformly observable systems, namely mobile robotics systems, is considered. The set of feasible configurations and the set of output flow equivalent states are defined. It is shown that the inter-relation between these two sets may serve as the basis for design of active observers. The proposed observer design methodology is illustrated by considering a unicycle robot model, equipped with a set of range-measuring sensors.</p><p>Finally, in the fourth paper, a geometrically intrinsic observer for Euler-Lagrange systems is defined and analyzed. This observer is a generalization of the observer recently proposed by Aghannan and Rouchon. Their contractivity result is reproduced and complemented by a proof that the region of contraction is infinitely thin. However, assuming <i>a</i> <i>priori </i>bounds on the velocities, convergence of the observer is shown by means of Lyapunov's direct method in the case of configuration manifolds with constant curvature.</p>

The main body of this thesis consists of four appended papers. The first two consider different aspects of the trajectory planning problem, while the last two deal with observer design for mobile robotic and Euler-Lagrange systems respectively. The first paper addresses the problem of designing a real time, high performance trajectory planner for aerial vehicles. The main contribution is two-fold. Firstly, by augmenting a novel safety maneuver at the end of the planned trajectory, this paper extends previous results by having provable safety properties in a 3D setting. Secondly, assuming initial feasibility, the planning method is shown to have finite time task completion. Moreover, in the second part of the paper, the problem of simultaneous arrival of multiple aerial vehicles is considered. By using a time-scale separation principle, one is able to adopt standard Laplacian control to this consensus problem, which is neither unconstrained, nor first order. Direct methods for trajectory optimization are traditionally based on a priori temporal discretization and collocation methods. In the second paper, the problem of adaptive node distribution is formulated as a constrained optimization problem, which is to be included in the underlying nonlinear mathematical programming problem. The benefits of utilizing the suggested method for online trajectory optimization are illustrated by a missile guidance example. In the third paper, the problem of active observer design for an important class of non-uniformly observable systems, namely mobile robotics systems, is considered. The set of feasible configurations and the set of output flow equivalent states are defined. It is shown that the inter-relation between these two sets may serve as the basis for design of active observers. The proposed observer design methodology is illustrated by considering a unicycle robot model, equipped with a set of range-measuring sensors. Finally, in the fourth paper, a geometrically intrinsic observer for Euler-Lagrange systems is defined and analyzed. This observer is a generalization of the observer recently proposed by Aghannan and Rouchon. Their contractivity result is reproduced and complemented by a proof that the region of contraction is infinitely thin. However, assuming a priori bounds on the velocities, convergence of the observer is shown by means of Lyapunov's direct method in the case of configuration manifolds with constant curvature. / QC 20101108

Les systèmes multi-capteurs exploitent les complémentarités des différentes sources sensorielles. Par exemple, le capteur visuo-inertiel permet d’estimer la pose à haute fréquence et avec une grande précision. Les méthodes de vision mesurent la pose à basse fréquence mais limitent la dérive causée par l’intégration des données inertielles. Les centrales inertielles mesurent des incréments du déplacement à haute fréquence, ce que permet d’initialiser la vision et de compenser la perte momentanée de celle-ci. Cette thèse analyse deux aspects du problème. Premièrement, nous étudions les méthodes visuelles directes pour l’estimation de pose, et proposons une nouvelle technique basée sur la corrélation entre des images et la pondération des régions et des pixels, avec une optimisation inspirée de la méthode de Newton. Notre technique estime la pose même en présence des changements d’illumination extrêmes. Deuxièmement, nous étudions la fusion des données a partir de la théorie de la commande. Nos résultats principaux concernent le développement d’observateurs pour l’estimation de pose, biais IMU et l’autocalibrage. Nous analysons la dynamique de rotation d’un point de vue non linéaire, et fournissons des observateurs stables dans le groupe des matrices de rotation. Par ailleurs, nous analysons la dynamique de translation en tant que système linéaire variant dans le temps, et proposons des conditions d’observabilité uniforme. Les analyses d’observabilité nous permettent de démontrer la stabilité uniforme des observateurs proposés. La méthode visuelle et les observateurs sont testés et comparés aux méthodes classiques avec des simulations et de vraies données visuo-inertielles. / Systems with multiple sensors can provide information unavailable from a single source, and complementary sensory characteristics can improve accuracy and robustness to many vulnerabilities as well. Explicit pose measurements are often performed either with high frequency or precision, however visuo-inertial sensors present both features. Vision algorithms accurately measure pose at low frequencies, but limit the drift due to integration of inertial data. Inertial measurement units yield incremental displacements at high frequencies that initialize vision algorithms and compensate for momentary loss of sight. This thesis analyzes two aspects of that problem. First, we survey direct visual tracking methods for pose estimation, and propose a new technique based on the normalized crosscorrelation, region and pixel-wise weighting together with a Newton-like optimization. This method can accurately estimate pose under severe illumination changes. Secondly, we investigate the data fusion problem from a control point of view. Main results consist in novel observers for concurrent estimation of pose, IMU bias and self-calibration. We analyze the rotational dynamics using tools from nonlinear control, and provide stable observers on the group of rotation matrices. Additionally, we analyze the translational dynamics using tools from linear time-varying systems, and propose sufficient conditions for uniform observability. The observability analyses allow us to prove uniform stability of the observers proposed. The proposed visual method and nonlinear observers are tested and compared to classical methods using several simulations and experiments with real visuo-inertial data.

Cette thèse porte sur la conception de commandes robustes pour les systèmes non linéaires, mettant l'accent sur les systèmes mécaniques. Des résultats concluants sont présentés pour résoudre deux situations très abordées dans la théorie du contrôle : 1) La stabilité des systèmes non linéaires perturbés ; 2) Le suivi global de trajectoire dans les systèmes mécaniques en ayant seulement connaissance de la position. Nous avons commencé par donner une méthode de conception des commandes robustes pour assurer une régulation de sortie non passive. En outre, si le système est perturbé (pas appariés), des preuves rigoureuses pour les rejeter sont fournies. Ce résultat est principalement inspiré d'un changement de coordonnées et de l'action intégrale dynamique. Si le scénario à traiter concerne des systèmes mécaniques avec des perturbations variant dans le temps, nous dotons le système de propriétés comme IISS (Integral Input- State Stable) et ISS (Input-State Stable). Ce résultat est obtenu en modifiant la procédure de conception de manière à rejeter les perturbations constantes (pas appariés). Cependant, en raison de la non-linéarité du système, les commandes qui en résultent ont une grande complexité. Pour le même problème, un deuxième et élégant résultat est donné au cas où un changement préalable de variable (impulsions) est réalisé. Finalement, une réponse convaincante au problème de suivi de trajectoire pour les systèmes mécaniques est donnée en tenant compte uniquement des informations de position. Nous résolvons ce problème en deux étapes. Premièrement, quelques modifications sont apportées à la preuve de stabilité d'un observateur de vitesse basée sur la théorie de l'invariance et l’Immersion récemment publié. Notez que ceci est un observateur satisfaisant la convergence exponentielle de vitesse dans les systèmes mécaniques. Deuxièmement et sur la base du changement de coordonnées (impulsions), un contrôleur de suivi avec stabilité exponentielle, tenant compte de la position et de la vitesse, est proposé. De telle sorte qu'avec la combinaison des deux résultats, le suivi de trajectoire exponentielle avec retour de position est donné. / This thesis focuses on the design of robust control for nonlinear systems, mainly on mechanical systems. The results presented are to two situations widely discussed in control theory: 1) The stability of nonlinear systems disturbed; 2) The global tracking trajectory in mechanical systems having only knowledge of the position. We started giving a design method of robust controls to ensure regulation on non-passive output. In addition, if the system is perturbed (constant unmatched), rigorous proof to its rejection is provided. This result is based mainly on change of coordinates and integral dynamic control. When the scenario to deal are mechanical systems with time-varying matched and unmatched, disturbance, the system is endowed with strong properties as IISS (Integral Input-State Stable) and ISS (Input-State Stable). This is achieved based on the design method to rejection of constant disturbances (unmatched). However, due to the nonlinearity of the system, the controllers have a high complexity. For the same problem, a second and elegant result is given making a initial change of coordinate on the momenta variable, such that the controller significantly simplifies, preserving the aforementioned robustness properties. Finally, a convincing answer to the problem of global exponential tracking of mechanical systems is given taking into account only the position information. We solve this problem in two steps. First, some slight variation is presented to the proof of stability of a speed observer based on Immersion and Invariance theory recently published. Note that this is a speed observer satisfying the exponential convergence speed in mechanical systems. Secondly, and based on the change of coordinates (momenta), a globally exponentially stable tracking controller with position and velocity known is proposed. The combination of both results give the first global exponential tracking controller of mechanical systems without velocity measurements.

Orientador: Gilberto Pechoto de Melo / Banca: Amarildo Tabone Paschoalini / Banca: Valder Steffen Júnior / Resumo: Neste trabalho desenvolveram-se metodologias de diagnóstico de falhas utilizando observadores de estado do tipo Filtro de Kalman, nas quais, as entradas para os observadores são identificadas utilizando as funções ortogonais de Fourier, Legendre e Chebyshev. Um tipo de observador denominado Proporcional-Integral é apresentado para a identificação de entradas desconhecidas. Este observador consegue estimar, sob certas condições, as entradas e ou distúrbios presentes no sistema e essas entradas são utilizadas para a diagnose de falha utilizando um observador do tipo Filtro de Kalman. Também é apresentado o desenvolvimento de uma metodologia de identificação de parâmetros bem como das forças de excitação, através das funções ortogonais, utilizando somente a resposta. Apresentam-se resultados obtidos por meio de simulações computacionais e realizados experimentalmente numa bancada de teste pertencente ao laboratório de vibrações mecânicas do Departamento de Engenharia Mecânica de Ilha Solteira. / Abstract: In this work a methodology for fault diagnosis of mechanical systems was developed by using Kalman Filter state observes, in which the input of the observers are identified by using Fourier, Legendre and Chebyshev orthogonal functions. A proportional-integral observer is presented to the unknown input identification. This observer is able to find the unknown inputs of the system and these inputs are used to fault detection purposes by using a Kalman Filter Observer. The methodology for the identification of system parameters and excitation forces by using only the response of the system, through orthogonal functions. The methodology developed is applied to a mechanical structure containing vibrating tables, in the Mechanical Vibrations Laboratory, at Unesp, Ilha Solteira. / Mestre

Nombreux sont les problèmes classiquement rencontrés dans les sciences de l'ingénieur dont la résolution fait appel à l'estimation d'état d'un système par le biais d'un observateur. La synthèse d'un observateur n'est envisageable qu'à la condition de disposer d'un modèle à la fois exploitable et représentatif du comportement dynamique du système. Or, la modélisation du système et la synthèse de l'observateur deviennent des tâches difficiles à accomplir dès lors que le comportement dynamique du système doit être représenté par un modèle de nature non linéaire. Face à ces difficultés, l'approche multimodèle peut être mise à profit. Les travaux présentés dans cette thèse portent sur les problèmes soulevés par l'identification, l'estimation d'état et le diagnostic de systèmes non linéaires représentés à l'aide d'un multimodèle découplé. Ce dernier, composé de sous-modèles qui peuvent être de dimensions différentes, est doté d'un haut degré de généralité et de flexibilité et s'adapte particulièrement bien à la modélisation des systèmes complexes à structure variable. Cette caractéristique le démarque des approches multimodèles plus conventionnelles qui ont recours à des sous-modèles de même dimension. Après une brève introduction à l'approche multimodèle, le problème de l'estimation paramétrique du multimodèle découplé est abordé. Puis sont présentés des algorithmes de synthèse d'observateurs d'état robustes vis-à-vis des perturbations, des incertitudes paramétriques et des entrées inconnues affectant le système. Ces algorithmes sont élaborés à partir de trois types d'observateurs dits à gain proportionnel, à gain proportionnel-intégral et à gain multi-intégral. Enfin, les différentes phases d'identification, de synthèse d'observateurs et de génération d'indicateurs de défauts sont illustrées au moyen d'un exemple académique de diagnostic du fonctionnement d'un bioréacteur / The state estimation of a system, with the help of an observer, is largely used in many practical situations in order to cope with many classic problems arising in control engineering. The observer design needs an exploitable model able to give an accurate description of the dynamic behaviour of the system. However, system modelling and observer design can not easily be accomplished when the dynamic behaviour of the system must be described by non linear models. The multiple model approach can be used to tackle these difficulties. This thesis deals with black box modelling, state estimation and fault diagnosis of nonlinear systems represented by a decoupled multiple model. This kind of multiple model provides a high degree of generality and flexibility in the modelling stage. Indeed, the decoupled multiple model is composed of submodels which dimensions can be different. Thus, this feature is a significant difference between the decoupled multiple model and the classical used multiple model where all the submodels have the same dimension. After a brief introduction to the multiple model approach, the parametric identification problem of a decoupled multiple model is explored. Algorithms for robust observers synthesis with respect to perturbations, modelling uncertainties and unknown inputs are afterwards presented. These algorithms are based on three kinds of observers called proportional, proportional-integral and multiple-integral. Lastly, identification, observers synthesis and fault sensitivity signals generation are illustrated via a simulation example of a bioreactor

Les travaux présentés dans cette thèse ont été effectués au Centre de Recherche en Automatique de Nancy (CRAN). Ils portent sur l'observation et la commande des systèmes singuliers non linéaires. Dans un premier temps nous nous sommes intéressés à la synthèse d'observateur et au filtrage H infini des systèmes singuliers bilinéaires. Dans un deuxième temps, nous avons étudié la synthèse d'observateur pour les systèmes singuliers non linéaires Lipschitziens. La dernière partie de ce travail concerne la stabilisation et la commande basée observateurs des systèmes singuliers non linéaires. L'objectif de ce travail a été de proposer des résultats facilement implémentables et de couvrir une large classe de systèmes non linéaires. La contribution principale de ce mémoire a été de proposer des observateurs H infini pour les systèmes singuliers non linéaires, en utilisant le non biais de l'erreur d'estimation. Les paramètres de ces observateurs sont obtenus par la résolution des inégalités matricielles linéaires (LMIs). Le deuxième apport concerne la synthèse de commande stabilisante et l'utilisation d'un des observateurs proposés dans cette thèse pour la synthèse d'une commande basée observateur pour les systèmes singuliers non linéaires. Cette dernière est réalisée grâce à la réécriture des fonctions non linéaires sous des formes adéquates à l'application de la commande des systèmes / This thesis work is realized in the Research Center in Automatic Control of Nancy (CRAN). It concerns the observation and control of nonlinear singular systems. Firstly, we were interested in the observer design and H infinity filtering for singular bilinear systems. In a second step, we studied the observers design for Lipschitz nonlinear singular systems. The last part of this work relates to the stabilization and observer based controller for a classe of singular nonlinear systems. The objective is to develop a simple and straightforward results which covers a large class of nonlinear systems. The main contribution of this thesis is in the H infinity observers design for nonlinear singular systems. It is based on the parametrization of the solution of the constrained generalized Sylvester equation. The second contribution relates to the design of stabilizing control and using the proposed observer to design an obsever based controller for nonlinear singular systems. Solutions of these problems are obtained by using Linear Matrix Inequalities (LMI) Formulation