Faults and failures in system components are the two main reasons for the instability and the degradation in control performance. In recent decades, fault-tolerant control (FTC) approaches were introduced to improve the resiliency of the control system against faults and failures. In general, FTC techniques are classified into two major groups: passive and active. Passive FTC systems do not rely on the fault information to control the system and are closely related to the robust control techniques while an active FTC system performs based on the information received from the fault detection and isolation (FDI) system, and the fault problem will be tackled more intelligently without affecting other parts of the system. This dissertation technically reviews fault and failure causes in control systems and finds solutions to compensate for their effects. Recent achievements in FDI approaches, and active and passive FTC designs are investigated. Thorough comparisons of several different aspects are conducted to understand the advantages and disadvantages of different FTC techniques to motivate researchers to further developing FTC, and FDI approaches. Then, a novel active FTC system framework based on online FDI is presented which has significant advantages in comparison with other state of the art FTC strategies. To design the proposed active FTC, a new FDI approach is introduced which uses the artificial neural network (ANN) and a model based observer to detect and isolate faults and failures in sensors and actuators. In addition, the extended Kalman filter (EKF) is introduced to tune ANN weights and improve the ANN performance. Then, the FDI signal combined with a nonlinear dynamic inversion (NDI) technique is used to compensate for the faults in the actuators and sensors of a nonlinear system. The proposed scheme detects and accommodates faults in the actuators and sensors of the system in real-time without the need of controller reconfiguration. The proposed active FTC approach is used to design a control system for three different applications: Unmanned aerial vehicle (UAV), load frequency control system, and proton exchange membrane fuel cell (PEMFC) system. The performance of the designed controllers are investigated through numerical simulations by comparison with conventional control approaches, and their advantages are demonstrated.

The High Redundancy Actuator (HRA) project investigates a novel approach to fault tolerant actuation, which uses a high number of small actuation elements, assembled in series and parallel in order to form a single intrinsically fault tolerant actuator. Element faults affect the maximum capability of the overall actuator, but through control techniques, the required performance can be maintained. This allows higher levels of reliability to be attained in exchange for less over-dimensioning in comparison to conventional redundancy techniques. In addition, the combination of both serial and parallel elements provides intrinsic accommodation of both lock-up and loose faults. Research to date has concentrated on HRAs based on electromechanical technology, of relatively low order, controlled through passive Fault Tolerant Control (FTC) methods. The objective of this thesis is to expand upon this work. HRA configurations of higher order, formed from electromagnetic actuators are considered. An element model for a moving coil actuator is derived from first principles and verified experimentally. This element model is then used to form high-order, non-linear HRA models for simulation, and reduced-order representations for control design. A simple, passive FTC law is designed for the HRA configurations, the results of which are compared to a decentralised, active FTC approach applied through a framework based upon multi-agent concepts. The results indicate that limited fault tolerance can be achieved through simple passive control, however, performance degradation occurs, and requirements are not met under theoretically tolerable fault levels. Active FTC offers substantial performance improvements, meeting the requirements of the system under the vast majority of theoretically tolerable fault scenarios. However, these improvements are made at the cost of increased system complexity and a reliance on fault detection. Fault Detection (FD) and health monitoring of the HRA is explored. A simple rule-based FD method, for use within the active FTC, is described and simulated. An interacting multiple model FD method is also examined, which is more suitable for health monitoring in a centralised control scheme. Both of these methods provide the required level of fault information for their respective purposes. However, they achieve this through the introduction of complexity. The rule-based method increases system complexity, requiring high levels of instrumentation, and conversely the interacting multiple model approach involves complexity of design and computation. Finally, the development of a software demonstrator is described. Experimental rigs at the current project phase are restricted to relatively low numbers of elements for practical reasons such as cost, space and technological limitations. Hence, a software demonstrator has been developed in Matlab/Simulink which provides a visual representation of HRAs with larger numbers of elements, and varied configuration for further demonstration of this concept.

La pile à combustible apparaît comme un système performant pour produire de l’électricité « verte » à partir de l’hydrogène dès lors que celui-ci est produit à partir de sources d’énergie renouvelables. Les avantages et la maturité de la technologie à membrane polymère font des PEMFC des candidates prometteuses. Cependant, plusieurs verrous scientifiques et technologiques limitent encore leur utilisation à grande échelle, en particulier leur coût, leur fiabilité et leur durée de vie. L’amélioration de ces caractéristiques passe par la mise en place d’outils de supervision, de détection de défauts et de contrôle des systèmes pile à combustible (PàC). Le travail de recherche est le fruit d’une collaboration entre le FC LAB de l’Université de Bourgogne Franche Comté et le LE2P de l’Université de La Réunion. Ce sujet de thèse s’inscrit dans la continuité des travaux menés au laboratoire FC LAB, portant en particulier sur le diagnostic et le pronostic de systèmes PàC, et des travaux menés au laboratoire LE2P, portant sur le test en ligne d’algorithmes de commande de PEMFC. Parmi les méthodes développées pour déployer la sureté de fonctionnement à un système physique, on retrouve les techniques de tolérance aux défauts, conçues pour maintenir la stabilité du système ainsi que des performances acceptables, même en présence de défauts. Ces techniques se décomposent généralement en trois phases : la détection d’erreurs ou de défaillances, l’identification des défauts à l’origine des problèmes, et l’atténuation. La littérature fait état d’un grand nombre d’outils de diagnostic et d’algorithmes de contrôle, mais l’association du diagnostic et du contrôle reste marginale. L’objectif de ce travail de thèse est donc le test en ligne de différentes stratégies de commande tolérante aux défauts, permettant de maintenir la stabilité du système et des performances acceptables même en présence de défauts. / Fuel cells (FC) are powerful systems for electricity production. They have a good efficiency and do not generate greenhouse gases. This technology involves a lot of scientific fields, which leads to the appearance of strongly inter-dependent parameters. It makes the system particularly hard to control and increase the fault’s occurrence frequency. These two issues underline the necessity to maintain the expected system performance, even in faulty condition. It is a so-called “fault tolerant control” (FTC). The present paper aims to describe the state of the art of FTC applied to the proton exchange membrane fuel cell (PEMFC). The FTC approach is composed of two parts. First, a diagnostic part allows the identification and the isolation of a fault. It requires a good a priori knowledge of all the possible faults in the system. Then, a control part, where an optimal control strategy is needed to find the best operating point or to recover the fault.