Automatic control techniques have been widely employed in industry to increase efficiency and profitability of the processes. However, reliability on automation increases the susceptibility of the system to faults in major control equipment such as actuators and sensors. This realization has motivated design of frameworks for fault detection and isolation (FDI) and fault tolerant control (FTC). The success of these FDI and FTC mechanisms is contingent on their ability to handle complexities associated with process systems such as nonlinearity, uncertainty, high dimensionality and the resulting effects of the existence of complexity in system structure such as faults that cannot be isolated. Motivated by the above considerations, this thesis considers the problem of fault diagnosis and fault tolerant control for complex process systems. First, an FDI framework is designed that can detect and confine possible locations for faults that cannot be isolated. Next, the problem of simultaneous actuator and sensor fault diagnosis for nonlinear uncertain systems. The key idea is to design FDI filters in a way they account for the impact of uncertainty explicitly. This work then considers the problem of simultaneous fault diagnosis in nonlinear uncertain networked systems. FDI is achieved using a distributed architecture, comprised of a bank of local FDI (LFDI) schemes that communicate with each other. The efficacy of the proposed FDI methodologies is shown via application to a number of chemical process examples. Finally, an integrated framework is proposed for fault diagnosis and fault tolerant control of variable air volume (VAV) boxes, a common component of heating, ventilation and air conditioning (HVAC) systems as an industrial case study of complex systems. The advantages of the proposed framework are diagnosing multiple faults and handling faults in stuck dampers using a safe parking strategy with energy saving capability. / Thesis / Doctor of Philosophy (PhD) / Automation is the key to increase efficiency and profitability of the processes. However, as the level of automation increases, major control equipment are more prone to faults. Thus, fault detection and isolation (FDI) and fault tolerant control (FTC) frameworks are required for fault handling. Fault handling, however, can only be efficiently achieved if the designed FDI and FTC frameworks are able to deal with complexities arising in process systems such as nonlinearity, uncertainty, high dimensionality and the resulting effects of the existence of complexity in system structure such as faults that cannot be isolated. This motivates design of FDI and FTC frameworks for complex process systems. First, FDI frameworks are presented that can diagnose faults in the presence of complexities mentioned above. Then, an integrated framework is designed for diagnosing and handling faults of heating, ventilation and air conditioning (HVAC) systems as an industrial case study of complex process systems.

Les résultats présentés dans cette thèse s’articulent autour de la synthèse d’observateurs de type grand gain pour des classes de systèmes non linéaires multi-entrées, multi-sorties non uniformément observables. Dans un premier temps, la classe de systèmes considérées est telle que la dynamique des variables d’état est décrite par la somme de deux termes. Le premier correspond à une partie affine en l’état décrite par le produit d’une matrice, dont les entrées (fonctions non linéaires de l’état) ont une structure triangulaire, par le vecteur d’état. Le deuxième terme est composé par les non linéarités du système qui ont aussi une structure triangulaire. Le gain de l’observateur proposé est issu de la résolution d’une équation différentielle ordinaire de type Lyapunov.La convergence exponentielle de l’erreur d’observation sous-jacente est établie sous une une certaine condition d’excitation persistante dépendant de l’entrée du système et de l’état de l’observateur.Dans un deuxième temps, la synthèse de cet observateur est étendue à une classe plus large de systèmes non linéaires où des états peuvent intervenir de manière non triangulaire.La notion d’indices caractéristiques associés à ces états est alors introduite et elle a permis de définir une structure triangulaire étendue pour la quelle la synthèse de l’observateur a aussi été effectuée.Enfin, il a été établi que les observateurs proposés peuvent être utiliséscomme observateurs adaptatifs pour l’estimation simultanée de l’état et de certains paramètres et une forme adaptative de ces observateurs a été générée.Les performances des différents observateurs proposés ont été illustrées à travers des exemples en simulation / The results given in this thesis deal with the design of high gain observers for some classes on Multi Input Multi Output non uniformly observable nonlinear systems. In a first step, the class of considered systems is such that the dynamics of the state variables is the sum of two terms. The first term is affine in the state and is composed by the product of a matrix, whose entries are nonlinear functions of the state with a triangular structure, by the state vector. The second term describes the system nonlinearities which also assume a triangular structure. The gain of the proposed observer is issued from the resolution of a Lyapunov ordinary differential equation. The exponential convergence of the underlying observation error is established under a persistent excitation condition involving the system inputs and the state of the observer. In a second step, the observer design has been extended to a larger class of nonlinear systems where some state variables may intervene in a non triangular way. The notion of the characteristic indices associated to these state variables is then introduced and it allowed to define an extended triangular structure for which a high gain observer has been designed. Finally, it has been established that the proposed observers can be used as adaptive ones to jointly estimate the system state together with some unknown parameters and an adaptive form of these observers has been derived. The performance and main properties of the proposed observers have been illustrated in simulation by considering many examples throughout this thesis.

<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)

Les observateurs et la régulation de sortie sont deux thèmes centraux de la théorie des système non linéaires. Bien que de nombreux chercheurs ont consacré leur attention à ces questions depuis plus de trente ans, il y a encore de nombreuses questions ouvertes. Dans la théorie des observateurs un rôle clé est joué par les observateurs à grand gain. Le but de la première partie de la thèse est d'etudier nouvelles techniques qui permettent de surmonter ou au moins d'atténuer les principaux problèmes qui caractérisent cette classe d'observateurs. Nous proposons une nouvelle classe d'observateurs à grand gain, appelé "low-power", qui permet de surmonter les problèmes numériques, d'éviter le phénomène de peaking et d'améliorer les propriétés de sensibilité aux bruit de mesure à haute fréquence. La deuxième partie de la thèse aborde du problème de la régulation de sortie, qui a été résolu pour les systèmes linéaires au cours des années 70, par Francis et Wonham qui ont énoncé le célèbre «principe de modèle interne". Des solutions constructives ont aussi été proposées dans le cadre non linéaire mais sous des hypothèses restrictives qui réduisent la classe des systèmes auxquels cette méthodologie peut être appliquée. Dans la thèse, nous nous concentrons sur le problème de la régulation de sortie en présence de perturbations périodiques, et nous proposons une nouvelle approche qui nous permet de considérer une classe plus large de systèmes non linéaires. La technique obtenué est robuste au sens défini par Francis et Wonham. / Observers and output regulation are two central topics in nonlinear control system theory. Although many researchers have devoted their attention to these issues for more than 30 years, there are still many open questions. In the observer theory a key role is played by the so called high-gain observers. The purpose of the first part of the thesis is to study novel techniques which allow to overcome or at least to mitigate some of the main drawbacks characterizing this class of observers. We propose a novel class of high-gain observers, denoted as ``low-power'', which allows to overcome numerical problems, to avoid the peaking phenomenon and to improve the sensitivity properties to high-frequency measurement noise. The second part of the thesis addresses the output regulation problem, solved for linear systems during the 70's by Francis and Wonham who coined the celebrated ``internal model principle''. Constructive solutions have also been proposed in the nonlinear framework but under restrictive assumptions that reduce the class of systems to which this methodology can be applied. In this thesis we focus on the output regulation problem in presence of periodic disturbances and we propose a novel approach which allows to consider a broader class of nonlinear systems. The resulting design is robust in the sense defined by Francis and Wonham.