A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s> A. Deterministic Fault Diagnosis Methods <s> Techniques to detect and isolate failures in complex technological systems, such as sensor biases, actuator malfunctions, leaks, and equipment deterioration are surveyed. The methods are based on analytical redundancy afforded by a mathematical model of the system. The main components of such techniques are residual generation using the model, signature generation by statistical testing, and signature analysis. Model-structural conditions for failure isolation are introduced together with transformation methods to implement them. Sensitivity and robustness considerations are presented, and a design framework based on model redundancy is proposed. > <s> BIB001 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s> A. Deterministic Fault Diagnosis Methods <s> Abstract The paper reviews the state of the art of fault detection and isolation in automatic processes using analytical redundancy, and presents some new results. It outlines the principles and most important techniques of model-based residual generation using parameter identification and state estimation methods with emphasis upon the latest attempts to achieve robustness with respect to modelling errors. A solution to the fundamental problem of robust fault detection, providing the maximum achievable robustness by decoupling the effects of faults from each other and from the effects of modelling errors, is given. This approach not only completes the theory but is also of great importance for practical applications. For the case where the prerequisites for complete decoupling are not given, two approximate solutions—one in the time domain and one in the frequency domain—are presented, and the crossconnections to earlier approaches are evidenced. The resulting observer schemes for robust instrument fault detection, component fault detection, and actuator fault detection are briefly discussed. Finally, the basic scheme of fault diagnosis using a combination of analytical and knowledge-based redundancy is outlined. <s> BIB002 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s> A. Deterministic Fault Diagnosis Methods <s> Abstract Problems of designing fault detection and identification filters in the frequency domain are formulated and solved. Using the factorization approach a characterization of all fault detection filters is derived. This enables the derivation of necessary and sufficient conditions for the existence of fault identification as well as detection and isolation filters. It is shown that these conditions are a generalization of existing results. The formulas of constructing the filters are also derived. In comparison with the algorithms given in previous work they are computationally straightforward and simple. Finally, the proposed method for designing fault identification filters is extended so that more practical cases can be handled. <s> BIB003 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s> A. Deterministic Fault Diagnosis Methods <s> Introduction to fault detection and diagnosis discrete linear systems random variables parameter estimation fundamentals analytical redundancy concepts parity equation implementation of residual generators design for structured residuals design for directional residuals residual generation for parametric faults robustness in residual generation statistical testing of residuals model identification for the diagnosis of additive faults diagnosing multiplicative faults by parameter estimation. <s> BIB004 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s> A. Deterministic Fault Diagnosis Methods <s> There is an increasing demand for dynamic systems to become safer and more reliable. This requirement extends beyond the normally accepted safety-critical systems such as nuclear reactors and aircraft, where safety is of paramount importance, to systems such as autonomous vehicles and process control systems where the system availability is vital. It is clear that fault diagnosis is becoming an important subject in modern control theory and practice. Robust Model-Based Fault Diagnosis for Dynamic Systems presents the subject of model-based fault diagnosis in a unified framework. It contains many important topics and methods; however, total coverage and completeness is not the primary concern. The book focuses on fundamental issues such as basic definitions, residual generation methods and the importance of robustness in model-based fault diagnosis approaches. In this book, fault diagnosis concepts and methods are illustrated by either simple academic examples or practical applications. The first two chapters are of tutorial value and provide a starting point for newcomers to this field. The rest of the book presents the state of the art in model-based fault diagnosis by discussing many important robust approaches and their applications. This will certainly appeal to experts in this field. Robust Model-Based Fault Diagnosis for Dynamic Systems targets both newcomers who want to get into this subject, and experts who are concerned with fundamental issues and are also looking for inspiration for future research. The book is useful for both researchers in academia and professional engineers in industry because both theory and applications are discussed. Although this is a research monograph, it will be an important text for postgraduate research students world-wide. The largest market, however, will be academics, libraries and practicing engineers and scientists throughout the world. <s> BIB005 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s> A. Deterministic Fault Diagnosis Methods <s> This paper presents a theoretical and tutorial treatment of the eigenstructure assignment approach for robust fault detection. The principles, existence conditions and design procedures are presented. The main contribution of the paper is the development of the assignment of right observer eigenvectors for robust residual generation. When some of the observer right eigenvectors are assigned parallel to the disturbance distribution directions, the diagnostic residual generated by the observer is insensitive to disturbances. Robust fault-detection design can be achieved by either left or right eigenvector assignment method. For left eigenvector assignment method, the sufficient conditions are presented. For right eigenvector assignment method, both necessary and sufficient conditions are proposed. Finally, two numerical examples are used to illustrate the eigenstructure assignment methods studied in the paper. Copyright © 2000 John Wiley & Sons, Ltd. <s> BIB006 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s> A. Deterministic Fault Diagnosis Methods <s> A design approach for observers using multiple-integrals is presented for descriptor systems, which allows the authors to decouple or attenuate measurement output disturbances. Design schemes for both pure integral observers and proportional integral observers are investigated. Measurement noise and input disturbances are also simultaneously taken into account in the design. A systematic design procedure for a causal or normal multiple-integral observer is addressed, which can be implemented conveniently using Matlab software. The considered disturbance may be unbounded, which means that the presented design approach is suitable for more general cases. Moreover, the system state, together with the disturbance vector and its finite time derivatives can be simultaneously estimated. The proposed design has great potential for application to control problems, such as those in diagnosis or observer-based control. In addition, it also has good estimation robustness and can be directly applied to normal systems. Simulation results show a satisfactory tracking performance as compared to the results obtained for descriptor systems. <s> BIB007 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s> A. Deterministic Fault Diagnosis Methods <s> In this note, the problem of observer design for linear descriptor systems with faults and unknown inputs is considered. First, it is considered that the fault vector function f is s~ times piecewise continuously differentiable. If the s~th time derivative of f is null, then s~ integral actions are included into a Luenberger observer, which is designed such that it estimates simultaneously the state, the fault, and its finite derivatives face to unknown inputs. Second, when the fault is not time piecewise continuously differentiable but bounded (like actuator noise) or s~th time derivative of fault is not null but bounded too, a high gain observer is derived to attenuate the fault impact in estimation errors. The considered faults may be unbounded, may not be determinist, and faults and unknown inputs may affect the state dynamic and plant outputs. Sufficient conditions for the existence of such observer are given. Results are illustrated with a differential algebraic power system. <s> BIB008 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s> A. Deterministic Fault Diagnosis Methods <s> In this paper, new descriptor observer design approaches are presented for multivariable systems with measurement noises. If the system matrix is stable, the proposed modified proportional and derivative observer technique allows us not only to decouple the measurement noise in any forms completely, but also obtain accurate estimations of both system states and measurement noises. If the system is detectable and the noise is bounded, it has been shown that two design parameters can provide more degrees of freedom. In this context, the derivative gain parameter is chosen to reduce the amplification of the noise, and the proportional gain is then selected to guarantee the stability of the error dynamics. For systems with both measurement output noises and input disturbances, a modified proportional, derivative and integral observer is constructed to asymptotically estimate states, input disturbances, and output noises at the same time. The applications of the proposed observers for systems with actuator and sensor faults are also discussed. Numerical examples are given to illustrate the design procedures, and the simulation results show the satisfactory tracking performance. <s> BIB009 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s> A. Deterministic Fault Diagnosis Methods <s> Fault management is critical for a vehicle active safety system. Since a sensor fault may not always be detectable by a sensor self-test or an electronic monitoring system whose detection often relies on out-of-range signals, a redundancy check is warranted for the detection of an in-range signal fault. In this paper, an in-vehicle roll rate sensor failure detection scheme utilizing analytical redundancy is presented. The vehicle is assumed to be equipped with a steering wheel angle sensor, a yaw rate sensor, a lateral accelerometer, and wheel speed sensors in addition to the roll rate sensor. Due to the wide variation of vehicle dynamics under a vast operating range, such as various and dynamically changing road super-elevations and road grades, the detection of a roll rate signal fault using analytical redundancy is particularly challenging. These challenges, as well as the robustness and performance of the proposed scheme are discussed. The robust performance of the proposed scheme, over model uncertainties and road disturbances, is illustrated analytically and validated through experimental test data. The analytical illustrations include three elements: a robust estimation of the vehicle roll angle, a dynamic compensation of both electrical and kinematics-induced biases in the roll rate signal, and a directionally sensitive design of a robust observer which decouples the model uncertainties and disturbances from the fault. The experimental verifications of no false positive and/or no false negative were taken with a variety of maneuvers and road conditions on several vehicle test platforms <s> BIB010 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s> A. Deterministic Fault Diagnosis Methods <s> The problem of sensor fault diagnosis in the class of nonlinear Lipschitz systems is considered. A dynamic observer structure is used with the objective to make the residual converge to the faults vector achieving detection and estimation at the same time. It is shown that, unlike the classical constant gain structure, this objective is achievable by minimizing the faults effect on the estimation error of the dynamic observer. The use of appropriate weightings to solve the design problem in a standard convex optimization framework is also demonstrated. An LMI design procedure solvable using commercially available software is presented. <s> BIB011 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s> A. Deterministic Fault Diagnosis Methods <s> In this paper, an adaptive unknown input observer (UIO) approach is developed to detect and isolate aircraft actuator faults. In a multiple-model scheme, a bank of parallel observers are constructed, each of which is based on a model that describes the system in the presence of a particular actuator fault. The observers are constructed based on a modified form of the standard UIO to generate fault-dependant residual signals, such that when a model matches the system, the residual signal will be zero. Otherwise, the residual will be definitely non-zero and governed uniquely by the faulty signal. For locked actuators and loss of actuator effectiveness, in which the locked position and the reduced effectiveness are additional unknowns, we develop an adaptive scheme to estimate these unknown parameters. To the best of our knowledge, this is the first adaptive UIO presented. We prove that the proposed adaptive algorithms guarantee that both the residual signals and the estimation errors of the unknown parameters converge exponentially when a model matches the plant. By further designing a model-matching index, the fault can be isolated accurately. A condition for the approach is that for an nth order system, there must be n independent measurements available. This requirement limits the applicability of our proposed approach. The condition is certainly satisfied by all state-feedback control systems. However, for some other systems, extra efforts may be needed to increase the number of measurements. The method is applied to a linear model of the F-16 aircraft with controller. The results show that the approach is effective. Copyright © 2006 John Wiley & Sons, Ltd. <s> BIB012 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s> A. Deterministic Fault Diagnosis Methods <s> For state-space systems with unknown process disturbances, a robust state-space observer is designed to simultaneously estimate the system state, the finitely times derivatives of the fault, and the fault signal. The considered fault signal can be allowed to be unbounded provided its finitely times derivative is bounded. A numerical example is given to illustrate the design procedure. Vehicle lateral dynamic system plays an important role in the vehicle manoeuverability, stability and driving safety. An application example with the real data for the vehicle lateral dynamic system is finally provided to demonstrate the efficiency of the present estimation technique. <s> BIB013 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s> A. Deterministic Fault Diagnosis Methods <s> This paper proposes a parity relation based fault estimation for a class of nonlinear systems which can be modelled by Takagi-Sugeno (TS) fuzzy models. The design of a parity relation based residual generator is formulated in terms of a family of linear matrix inequalities (LMIs). A numerical example is provided to illustrate the effectiveness of the proposed design techniques. <s> BIB014 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s> A. Deterministic Fault Diagnosis Methods <s> The existence of damage in different members of a structure can be posed as a fault detection problem. It is also necessary to isolate structural members in which damage exists, which can be posed as a fault isolation problem. It is also important to detect the time instants of occurrence of the faults/damage. The structural damage detection filter developed in this paper is a model-based fault detection and isolation (FDI) observer suitable for detecting and isolating structural damage. In systems, possible faults, disturbances and noise are coupled together. When system disturbances and sensor noise cannot be decoupled from faults/damage, the detection filter needs to be designed to be robust to disturbances as well as sensitive to faults/damage. In this paper, a new H−/H∞ and iterative linear matrix inequality (LMI) technique is developed and a new stabilizing FDI filter is proposed, which bounds the H∞ norm of the transfer function from disturbances to the output residual and simultaneously does not degrade the component of the output residual due to damage. The reduced-order error dynamic system is adopted to form bilinear matrix inequalities (BMIs), then an iterative LMI algorithm is developed to solve the BMIs. The numerical example and experimental verification demonstrate that the proposed algorithm can successfully detect and isolate structural damage in the presence of measurement noise. <s> BIB015 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s> A. Deterministic Fault Diagnosis Methods <s> In this paper, a novel discrete proportional and integral observer is proposed for estimating the system state, input and output disturbances at the same time. Compared with the previous results, the proposed observer has an advantage in handling output disturbances. A simulated numerical example is given to demonstrate the efficiency. By using the estimates of the state and disturbance, an observer-based controller with disturbance accommodation is designed to ensure the system stability and to satisfy the specified performance index. A simulated study of a reduced-order gas turbine discrete model is given to illustrate the design approach, and encouraging simulation results are obtained. Copyright q 2007 John Wiley & Sons, Ltd <s> BIB016 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s> A. Deterministic Fault Diagnosis Methods <s> Based on the techniques of high gain observer and adaptive estimation, an adaptive observer is proposed in this paper for sensor fault estimation in a class of uniformly observable non-linear systems. It is first assumed that a high gain observer exists for the fault-free system. With a parametric model of sensor fault, a high gain adaptive observer is then designed for sensor fault estimation. In order to establish the global convergence of the adaptive observer, in addition to the usual conditions for high gain observer convergence, a persistent excitation condition is also required, like in most recursive parameter estimation problems. <s> BIB017 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s> A. Deterministic Fault Diagnosis Methods <s> This paper studies the problem of fault estimation using adaptive fault diagnosis observer. A fast adaptive fault estimation (FAFE) approximator is proposed to improve the rapidity of fault estimation. Then based on linear matrix inequality (LMI) technique, a feasible algorithm is explored to solve the designed parameters. Furthermore, an extension to sensor fault case is investigated. Finally, simulation results are presented to illustrate the efficiency of the proposed FAFE methodology. <s> BIB018 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s> A. Deterministic Fault Diagnosis Methods <s> A novel fuzzy-observer-design approach is presented for Takagi-Sugeno fuzzy models with unknown output disturbances. In order to decouple the unknown output disturbance, an augmented fuzzy descriptor model is constructed by supposing the disturbance to be an auxiliary state vector. A fuzzy state-space observer is next designed for the augmented fuzzy descriptor system, and the simultaneous estimates of the original state and disturbance are thus obtained. The proposed observer technique is further applied to estimate sensor faults. Finally, a numerical example is given to illustrate the design procedure, and the simulation results show the desired tracking performance. The pre knowledge of the disturbance and fault is not necessary for our design. Moreover, the considered disturbance and sensor fault can be in any form. <s> BIB019 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s> A. Deterministic Fault Diagnosis Methods <s> In this study, a novel identification technique, that is high-gain observer-based identification approach, is proposed for systems with bounded process and measurement noises. For system parameters with abnormal changes, an adaptive change detection and parameter identification algorithm is next presented. The presented technique and algorithm are finally applied to the parameter identification of the gas turbine engine by using the recorded input data from the engine test-bed. The identified parameters and the response curves are desirable. The simulations have proved the effectiveness of the proposed procedure compared with the previous identification approach. <s> BIB020 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s> A. Deterministic Fault Diagnosis Methods <s> This paper investigates robust fault diagnosis strategies for the auto-balancing of an ergonomically designed two-wheeled cart which is inherently unstable and has a non-minimum phase. To endow the rider with robust stabilization, the normalized coprime factorization for steering is employed for allowing maximum model uncertainties and the driving orientation is achieved with an electronic differential steering control. A model-based fault-detection filter is designed to detect sensor faults. The observer gain obtained by solving an algebraic Riccati equation in the normalized coprime factorization approach offers some design convenience associated with the fault diagnosis filter. In order to promptly alert the rider for safety purposes in the event of a malfunction, the decision-making process to identify a critical failure is also investigated. Finally, evaluation examples are given to illustrate the performance of the proposed robust fault diagnosis strategies. <s> BIB021 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s> A. Deterministic Fault Diagnosis Methods <s> This study is motivated by the onboard fault detection of gas turbine engines (GTEs), where the computation resources are limited and the disturbance is assumed to be band-limited. A fast Fourier transformation (FFT)-based disturbance frequency estimation approach is proposed and performance indexes are improved by integrating such frequency information. Furthermore, in the left eigenvector assignment, both eigenvalues and free parameters are optimized. As illustrated in the application to the actuator fault detection of a GTE, significant improvements are achieved compared to the existing methods. By combining the frequency estimation and eigenvalue optimization, the main contribution of the paper is the reduction of the computation complexity and the avoidance of the local optimal solution due to fixed eigenvalues. <s> BIB022 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s> A. Deterministic Fault Diagnosis Methods <s> Abstract In this paper, the problem of robust fault detection filter (RFDF) design for a class of linear systems with some nonlinear perturbations and mixed neutral and discrete time-varying delays is investigated. By using a descriptor technique, Lyapunov–Krasovskii functional and a suitable change of variables, new required sufficient conditions are established in terms of delay-dependent linear matrix inequalities (LMIs) to synthesize the residual generation scheme. Based on the Luenberger type observers, the explicit expression of the filters is derived for the fault such that both asymptotic stability and a prescribed level of disturbance attenuation are satisfied for all admissible nonlinear perturbations. A numerical example is provided to demonstrate the effectiveness and the applicability of the proposed method. <s> BIB023 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s> A. Deterministic Fault Diagnosis Methods <s> This study addresses the robust fault detection problem for continuous-time switched systems with state delays. The fault detection filter is used as the residual generator depending on the system mode. Attention is focused on designing the filter such that, for the modelling errors, the unknown inputs and the control one, the error between the residuals and the faults is minimised. The addressed fault detection filter design is converted into an auxiliary H ? filtering problem. By using the Lyapunov-Krasovskii functional method and average dwell time approach, a sufficient condition for the solvability of this problem is established in terms of linear matrix inequalities (LMIs). Two examples are provided to demonstrate the effectiveness of the proposed method. <s> BIB024 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s> A. Deterministic Fault Diagnosis Methods <s> An approach for nonlinear unknown input observer (NUIO) design is proposed for a class of nonlinear systems representable by a Takagi—Sugeno (TS) fuzzy system. The proposed NUIO design for TS fuzzy... <s> BIB025 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s> A. Deterministic Fault Diagnosis Methods <s> Unknown input observers (UIO) can be used in the model-based fault detection and isolation (FDI) schemes to reduce or almost eliminate the effect of unknown disturbances on the multi input multi output (MIMO) plant/system. In this paper, a new FDI of the MIMO system was carried out in as well as the design of many fault isolation banks of UIOs has been done. These banks are used to generate residuals that are insensitive to unknown disturbances or noise. To make sure best detection and isolation of the faults, these banks generate residuals, which are sensitive to only one fault. The fault in the actuator is detected and isolated with a lower false alarm rate effectively. <s> BIB026 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s> A. Deterministic Fault Diagnosis Methods <s> Abstract This paper proposes an operator based fault detection method for an actuator fault of an aluminum plate thermal process with input constraints. Operator-based robust right coprime factorization (RCF) approach is utilized in this method. After developing a mathematical model of the thermal process, a robust tracking operator system is designed for the process with input constraints. Following this, design of the fault detection system is given by using operator-based robust RCF approach. Finally, experiment is conducted to support the proposed design method. <s> BIB027 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s> A. Deterministic Fault Diagnosis Methods <s> The problem of residual evaluation for fault detection in nonlinear systems is addressed in this article. Using the factorisation approach, a post-filter is designed and a threshold is computed to achieve an optimal trade-off between fault detectability and the number of false alarms. Furthermore, it is shown that the proposed post-filter also guarantees ℋ−/ℋ∞ multi-objective optimisation of the residual signal. The effectiveness of the proposed method is demonstrated by fault detection of the three-tank benchmark system. <s> BIB028 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s> A. Deterministic Fault Diagnosis Methods <s> This work considers the problem of sensor fault detection and isolation (FDI) and fault-tolerant control for nonlinear systems subject to input constraints. The key idea of the proposed method is to exploit model-based sensor redundancy through state observer design. To this end, an output feedback control design using high-gain observers is first presented. An FDI scheme that utilizes the enhanced applicability of the observer design is then proposed, which is composed of a bank of high-gain observers. Upon FDI, the state estimate generated using measurements from the healthy sensors is used to preserve practical stability of the closed-loop system. The implementation of the FDI and fault-handling framework is illustrated using a chemical reactor example. <s> BIB029 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s> A. Deterministic Fault Diagnosis Methods <s> This paper addresses robust fault diagnosis of the chaser's thrusters used for the rendezvous phase of the Mars Sample Return (MSR) mission. The MSR mission is a future exploration mission undertaken jointly by the National Aeronautics and Space Administration (NASA) and the European Space Agency (ESA). The goal is to return tangible samples from Mars atmosphere and ground to Earth for analysis. A residual-based scheme is proposed that is robust against the presence of unknown time-varying delays induced by the thruster modulator unit. The proposed fault diagnosis design is based on Eigenstructure Assignment (EA) and first-order Pade approximation. The resulted method is able to detect quickly any kind of thruster faults and to isolate them using a cross-correlation based test. Simulation results from the MSR "high-fidelity" industrial simulator, provided by Thales Alenia Space, demonstrate that the proposed method is able to detect and isolate some thruster faults in a reasonable time, despite of delays in the thruster modulator unit, inaccurate navigation unit, and spatial disturbances (i.e. J2 gravitational perturbation, atmospheric drag, and solar radiation pressure). <s> BIB030 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s> A. Deterministic Fault Diagnosis Methods <s> This paper investigates the problem of robust fault detection observer design for nonlinear Takagi-Sugeno models with unmeasurable premise variables subject to sensor faults and unknown bounded disturbance. The main idea is to synthesize a robust fault detection observer by means of a mixed H =H1 performance index. The considered observer is used to estimate jointly states and faults. Using the technique of descriptor system representation, we proposed a new less-conservative approach in term of a linear matrix inequality (LMI) by considering the sensor fault as an auxiliary state variable. A solution of the problem is obtained by using an iterative LMI procedure. <s> BIB031 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s> A. Deterministic Fault Diagnosis Methods <s> Detecting cracks in rotating shafts is a challenging problem when using vibration-based diagnostics. This is due to the fact that a localized crack has a minimal influence on the global vibration response of the system. To increase sensitivity and reliability, the vibration response needs to be coupled with additional sources of information such as a mathematical model of the machine. Modern control theory techniques offer system-level mathematical models for both control and diagnostics. Focusing on the latter, a new and promising approach involves the use of unknown input observers. Such observers can be designed to employ robust fault detection filters (RFDFs) for isolating fault signatures while reducing the influence of real-world disturbances and noise. For the present study, a modified design procedure coupled with robust fault detection is utilized for shaft crack detection. The filter is designed using the linear matrix inequalities (LMI) technique. The LMI approach is applied to obtain the solution of the mixed H−/H∞ optimization problem, which arises during the synthesis of the RFDF. By reformulating the LMI conditions, the proposed RFDF design procedure is simplified and thus requires less iteration steps to find the optimal solution. A new feature of the present approach involves the application of the rigid finite element method for the formulation of the mathematical model of the rotor and the shaft crack. The numerical and experimental results confirm the advantages of the designed robust fault detection filter and its ability to detect shaft cracks. The filter is minimally sensitive to measurement noise while allowing for the identification of shallow cracks (2% or 5% deep). The cracks are manifested through the observance of very subtle vibration response changes. The results also confirm the effectiveness and accuracy of the rigid finite element modeling concerning the cracked rotor. <s> BIB032 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s> A. Deterministic Fault Diagnosis Methods <s> In this brief, a fault detection and isolation (FDI) method is developed for aircraft engines by utilizing nonlinear adaptive estimation techniques. The fault diagnosis method follows a general architecture developed in previous papers, where a fault detection estimator is used for fault detection, and a bank of nonlinear adaptive fault isolation estimators are employed to determine the particular fault type/location. Each isolation estimator is designed based on the functional structure of a particular fault type under consideration. The general FDI architecture is applied to a realistic nonlinear aircraft engine model recently developed by NASA Researchers. In addition, the robustness of the fault diagnostic method with respect to normal engine health degradation is enhanced by adaptive thresholds and adaptive approximation techniques, hence accurate diagnostic performance is maintained while the engine continues to degrade over its lifetime. Some representative simulation results are given to show the effectiveness of the robust nonlinear FDI method. <s> BIB033 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s> A. Deterministic Fault Diagnosis Methods <s> In this paper, a discrete-time framework for diagnosis of faults of joint sensors, wrist-mounted force/torque sensors, and actuators of robotic manipulators is devised. It is assumed that redundant joint sensor measurements are available. Sensor measurements, together with the estimates computed by two isolation observers, are processed by a decision-making system, providing detection and isolation of the faults of the joint sensors as well as healthy measurements. Then, healthy measurements are used to feed a bank of diagnostic observers aimed at detecting, isolating, and identifying faults of joint actuators and force/torque sensors. The framework is experimentally tested on a cooperative industrial setup, composed of two industrial robots with six degrees of freedom performing a cooperative task. <s> BIB034 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s> A. Deterministic Fault Diagnosis Methods <s> SUMMARY ::: ::: A design framework of the observer-based robust fault estimation for continuous-time/discrete-time systems is presented in this paper. Firstly, a multiconstrained fault estimation observer under the H∞ performance specification with the regional pole constraint is proposed to achieve robust fault estimation. Then, the existence conditions for both continuous-time/discrete-time systems are derived explicitly. Furthermore, by introducing slack variables, improved results on the multiconstrained fault estimation observer design are obtained such that different Lyapunov functions can be separately designed for each constraint. Finally, simulation results of a vertical takeoff and landing aircraft are presented to illustrate our contributions. Copyright © 2012 John Wiley & Sons, Ltd. <s> BIB035 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s> A. Deterministic Fault Diagnosis Methods <s> Abstract The present paper proposes two new schemes of sensor fault estimation for a class of nonlinear systems and investigates their performances by applying these to satellite control systems. Both of the schemes essentially transform the original system into two subsystems (subsystems 1 and 2), where subsystem-1 includes the effects of system uncertainties, but is free from sensor faults and subsystem-2 has sensor faults but without any uncertainties. Sensor faults in subsystem-2 are treated as actuator faults by using integral observer based approach. The effects of system uncertainties in subsystem-1 can be completely eliminated by a sliding mode observer (SMO). In the first scheme, the sensor faults present in subsystem-2 are estimated with arbitrary accuracy using a SMO. In the second scheme, the sensor faults are estimated by designing an adaptive observer (AO). The sufficient condition of stability of the proposed schemes has been derived and expressed as a linear matrix inequality (LMI) optimization problem and the design parameters of the observers are determined by using LMI techniques. The effectiveness of the schemes in estimating sensor faults is illustrated by considering an example of a satellite control system. The results of the simulation demonstrate that the proposed schemes can successfully estimate sensor faults even in the presence of system uncertainties. <s> BIB036 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s> A. Deterministic Fault Diagnosis Methods <s> A most critical and important issue surrounding the design of automatic control systems with the successively increasing complexity is guaranteeing a high system performance over a wide operating range and meeting the requirements on system reliability and dependability. As one of the key technologies for the problem solutions, advanced fault detection and identification (FDI) technology is receiving considerable attention. The objective of this book is to introduce basic model-based FDI schemes, advanced analysis and design algorithms and the needed mathematical and control theory tools at a level for graduate students and researchers as well as for engineers. <s> BIB037 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s> A. Deterministic Fault Diagnosis Methods <s> In this paper, a robust fault detection filter is designed for a 3MW wind turbine system. The parameter eigenvalue assignment approaches and evolutionary optimal algorithms are integrated to seek optimal observer gain such that the residual signal is sensitive to the fault, but robustness against the disturbances. From all the simulations, the performance of fault detections is satisfactory. <s> BIB038 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s> A. Deterministic Fault Diagnosis Methods <s> Lithium-ion batteries possess high power, energy, and long cycle life. They are best candidates for applications on hybrid and electric vehicles. To ensure reliable operation, one of the functions in a battery management system is health monitoring in terms of fault diagnosis and estimation. The purpose of this brief is to provide a fault-diagnostic scheme that can achieve single fault isolation and estimation for a three-cell battery string subject to uncertainties. Detecting and isolating faults in systems subject to uncertainties is a challenging task due to the difficulty in distinguishing the effects of faults from uncertainties. To facilitate fault isolation, a bank of systems, each corresponding to a particular fault, are formulated by reorganizing the considered system. Each system in the bank is first transformed into two subsystems. Then, a classical Luenberger observer is designed for the first subsystem to generate a fault-detection residual. In this manner, a bank of reduced-order Luenberger observers are designed to locate a specific fault source, and thus fault isolation is achieved. Parallel to the bank of reduced-order Luenberger observers, a bank of learning observers (LOs) are also constructed to provide an estimate of the isolated fault. As a result, the synthesized design of Luenberger observers and LOs can realize simultaneous fault isolation and estimation. Parameters of an A123 battery cell are extracted via experiments, and effectiveness of the proposed design is demonstrated through simulation studies on the model of a three-cell battery string. <s> BIB039 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s> A. Deterministic Fault Diagnosis Methods <s> Abstract Online robust sensor fault detection is a challenging problem in control engineering systems. In this paper, a new method is proposed to design a Nonlinear Unknown Input Observer (NUIO) for robust sensor fault detection. The proposed method is based on cubature rule. NUIO decouples disturbances and uncertainties from estimated states in nonlinear systems. The main contribution of this work is to exploit cubature rule in the UIO structure to overcome nonlinear calculations in the presence of external disturbances for sensor fault detection purposes. For illustrating the performance of this approach, it is applied to a nonlinear Continuous Stirred Tank Reactor (CSTR) under faulty sensors. Compared to the previous NUIO methods, which are based on Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF), simulation results demonstrate the superiority of the proposed approach. <s> BIB040 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s> A. Deterministic Fault Diagnosis Methods <s> This paper considers the estimation of the state of charge and state of health for lithium-ion batteries, while an inclusive model is taken into account. The model includes two RC subnetworks, which represent the fast and slow transient responses of the terminal voltage. Nevertheless, the linear part of the model is unobservable. On the other hand, the nonlinear behavior of the open-circuit voltage versus state of charge is also included in the model. The proposed observer tackles the aforementioned problems to attain a reliable estimation of the state of charge. Moreover, as opposed to the methods in which the nonlinearities or uncertainties in the model are disregarded or those terms are discarded using a conventional sliding-mode observer, an analytical method is considered to estimate the additive nonlinear or uncertainty term in the model. This approach leads to a very accurate model of the battery to be used in a battery management system. Moreover, an online parameter estimation method is proposed to estimate the battery's state of health. The proposed scheme benefits from an adaptive rule for the online estimation of the series resistance in the lithium-ion battery based on the accurately identified model. Experimental tests certify the performance and feasibility of the proposed schemes. <s> BIB041 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s> A. Deterministic Fault Diagnosis Methods <s> SUMMARY ::: ::: This paper presents a robust fault detection and isolation scheme using a sliding mode observer based on a linear parameter varying system, with fault reconstruction capability. Both actuator and sensor fault reconstruction schemes are considered that possess robustness against a certain class of uncertainty and corrupted measurements. For actuator fault reconstruction, the input distribution matrix (associated with the actuators being monitored) is factorized into fixed and varying components. LMIs are used to design the key observer parameters in order to minimize the effect of uncertainty and measurement corruption on the fault reconstruction signal. The faults are reconstructed using the output error injection signal associated with the nonlinear term of the sliding mode observer. For sensor fault reconstruction, the idea is to reformulate the problem into an actuator fault reconstruction scenario so that the same design procedure can be applied. This is achieved by augmenting the original system with the filtered sensors being monitored. Simulations using a full nonlinear model of a large transport aircraft are presented and show good fault reconstruction performance. Copyright © 2013 John Wiley & Sons, Ltd. <s> BIB042 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s> A. Deterministic Fault Diagnosis Methods <s> A sliding mode observer in the presence of sampled output information and its application to robust fault reconstruction is studied. The observer is designed by using the delayed continuous-time representation of the sampled-data system, for which sufficient conditions are given in the form of linear matrix inequalities (LMIs) to guarantee the ultimate boundedness of the error dynamics. Though an ideal sliding motion cannot be achieved in the observer when the outputs are sampled, ultimately bounded solutions can be obtained provided the sampling frequency is fast enough. The bound on the solution is proportional to the sampling interval and the magnitude of the switching gain. The proposed observer design is applied to the problem of fault reconstruction under sampled outputs and system uncertainties. It is shown that actuator or sensor faults can be reconstructed reliably from the output error dynamics. An example of observer design for an inverted pendulum system is used to demonstrate the merit of the proposed methodology compared to existing sliding mode observer design approaches. <s> BIB043
Observer plays a key role in model-based fault diagnosis for monitored systems/processes characterized by deterministic models. The schematic of the observer-based fault diagnosis is depicted by Fig. 3 , which includes fault detection, fault isolation, and fault identification (or called fault reconstruction or fault estimation). For simplicity, the model of the process in Fig. 3 is assumed to be a linearized state-space model, which is described by the following: , and ω(k) ∈ R ω are the system state, control input, measured output, unexpected actuator fault, component/parameter fault, sensor fault, process An observer-based fault detection filter is given in the following form: where x(k) and y(k) are the estimates of the state and output, respectively; r(k) is the residual signal, and K is the observer gain to be designed. Let e(k) = x(k) − x(k), the frequencydomain residual signal can be described by where It is indicated from (3) that the residual signal is subjected to both fault signals and disturbance signals (including modeling errors, process disturbances, and measurement noises). In order that the residual signal is sensitive to faults, but robust against disturbances, the observer gain can be designed by solving an optimization problem over a specific frequency range, i.e., In order to solve (4), the parametric eigenstructure assignment approach for fault diagnosis was initialized by  and further revisited in BIB006 , in which the observer gain K is formulated as the function of the eigenvalues and eigenvectors; therefore, seeking an optimal K is transformed to the problem of finding optimal eigenvalues and eigenvectors. Recently, eigenstructure assignment-based fault diagnosis approaches have been applied to vehicles BIB010 , gas turbine engines BIB022 , spacecraft BIB030 , and wind turbine systems BIB038 . Alternatively, the multiobject optimization problem described by (4) can be reformulated by linear matrix inequality (LMI), which has been a popular method for fault diagnosis research and applications owing to its wide applicability to a variety of dynamic systems. Recent development of the LMI-based fault diagnosis can be found for various systems such as Lipschitz nonlinear systems BIB011 , Takagi-Sugeno (TS) fuzzy nonlinear systems  , BIB031 , timedelay systems BIB023 , switching systems BIB024 , and application to structure damage detection BIB015 and shaft crack detection BIB032 . A bank of observer-based residuals is generally required in order to realize fault isolation. A natural idea is to make a single residual sensitive to the fault concerned, but robust against other faults, disturbances, and modeling errors, which is called structure residual fault isolation BIB001 . Alternative fault isolation logic is to make each residual signal sensitive to all but one fault and robust against modeling errors and disturbances, which is called generalized residual fault isolation BIB002 . Recent results on robust fault isolation are developed for nonlinear systems  , BIB029 and various applications such as for aircraft engine BIB033 , robotic manipulators BIB034 , and lithium-ion batteries BIB039 . The unknown input observer, which is proposed by  , is another fault isolation tool by decoupling input disturbance, modeling errors, and other faults in the corresponding residuals. Recently, the unknown-input-observer-based fault isolation techniques are extended to nonlinear systems BIB025 , BIB040 and applied to aircraft systems BIB012 , inductor motors BIB026 , and waste water treatment plant  . Fault identification (or called fault reconstruction/fault estimation) is to determine the type, size, and shape of the fault concerned, which is vital information for fault-tolerant operation. Advanced observer techniques such as proportional and integral (PI) observers BIB016 , BIB035 , proportional multiple-integral (PMI) observers BIB007 BIB008 BIB013 , adaptive observer BIB017 BIB018 BIB041 , sliding mode observers BIB042 , BIB043 , and descriptor observers BIB009 , BIB019 are usually utilized for fault estimation/reconstruction. The essence of the advanced observers is to construct an augmented system by introducing the concerned fault as an additional state, and the extended state vector is thereafter estimated, leading to the estimates of the concerned fault signal together with original system states. Therefore, the advanced observers are also called simultaneous state and fault observers. The aforementioned advanced observer techniques are in an advantage position either for reconstructing slow-varying additive faults (PI and PMI observers), slow-varying parameter faults (adaptive observers), actuator faults with sinusoidal waveforms (sliding mode observers), and high-frequency sensor faults (descriptor system approaches). The aforementioned observer techniques may be integrated or combined in order to solve engineering-oriented problems. For instance, in BIB036 , integral observer, sliding observers, and adaptive observers are combined to reconstruct sensor faults for satellite control systems. In BIB020 , PI observer and descriptor observer techniques are integrated to estimate parameter faults for an aero engine system. Another well-known model-based fault diagnosis is parity relation approach, which was developed in the early 1980s  ,  . The parity relation approach is to generate residuals (parity vector), which are employed to check the consistency between the model and process outputs. The parity relation approach can be applied to either time-domain state-space model or frequency-domain input-output model, which is well revisited by the books BIB005 , BIB037 , BIB004 . Recently, the parity relation method has been extended for fault diagnosis for more complex models such as TS fuzzy nonlinear systems BIB014 and fuzzy tree models  and applied to various industrial systems such as aircraft control surface actuators  and electromechanical brake systems  . Stable factorization approach is frequency-domain fault diagnosis method, which was initiated in 1987 by  and further extended by BIB003 in 1990. The basic idea is to generate a residual, based on the stable coprime factorization of the transfer function matrix of the monitored system, which is made sensitive to the fault, but robust against disturbances, by selecting an optimal weighting factor. Recent developments of stable factorization approach can be found in BIB028 for nonlinear systems and BIB021 , BIB027 for applications in autobalancing twowheeled cart and thermal process, respectively. It is worthy to point out that the parity relation method and the stable factional approach both have some kind of connections with observers. For instance, the parity relation approach is equivalent to the use of a dead-beat observer, and the coprime factorization realization includes the design of observer gain (together with state-feedback gain).