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

Robust Model-Based Fault Diagnosis for Dynamic Systems

On robust estimation of the location parameter

The Theory of Matrices. By F R. Gantmacher. Two volumes, pp. 374 and 276. 1959. (Translated from the Russian by K. A. Hirsch; Chelsea Publishing Company, New York)

https://users.encs.concordia.ca/~ymzhang/publications/ARC32-2-98Zhang_pp.229-252.pdf

Bibliographical review on reconfigurable fault-tolerant control systems

With the continuous increase in complexity and expense of industrial systems, there is less tolerance for performance degradation, productivity decrease, and safety hazards, which greatly necessitates to detect and identify any kinds of potential abnormalities and faults as early as possible and implement real-time fault-tolerant operation for minimizing performance degradation and avoiding dangerous situations. During the last four decades, fruitful results have been reported about fault diagnosis and fault-tolerant control methods and their applications in a variety of engineering systems. The three-part survey paper aims to give a comprehensive review of real-time fault diagnosis and fault-tolerant control, with particular attention on the results reported in the last decade. In this paper, fault diagnosis approaches and their applications are comprehensively reviewed from model- and signal-based perspectives, respectively.

/pdf/a-survey-of-fault-diagnosis-and-fault-tolerant-techniques-9uuf1uqysf.pdf

A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches

In this paper, a new method is proposed to determine the structure of PCA models for system diagnosis. This method based on the principle of variable reconstruction determines PCA models in order to optimize detection and isolation of simple and multiple faults affecting redundant or non redundant variables. This new method has been validated by a simulation example of a nonlinear system.

A new method for determining PCA models for system diagnosis

This paper proposes a method to discuss the stability analysis of multiple models. The proposed stability analysis is based on the use of scalar Lyapunov functions and the properties of M-matrices. An example is included to illustrate the proposed method.

/pdf/on-the-stability-analysis-of-a-class-of-multiple-models-1fbimco6v0.pdf

On the stability analysis of a class of multiple models

The problem of simultaneously estimating the state and the fault of linear time varying stochastic systems in the presence of unknown input with uncertain noise covariances is presented. The approach suggested rests on the use of the Proportional Integral Three-Stage Kalman Filter (PI-ThSKF). This technique is qualified to be robust against the noise covariance matrices uncertainty. The proposed filter is tested by an illustrative example.

Robust fault and state estimation for linear discrete-time systems with unknown disturbances using PI Three-Stage Kalman Filter

As systems become more and more complex, the use of nonlinear models for modeling is often unavoidable. However, nonlinear models naturally increase the difficulty of designing state estimation observers, control laws, and fault-tolerant control strategies. In fact, a specific analysis of the nonlinearities is needed to propose appropriate theoretical tools to deal with these problems. An interesting way to avoid analysis of the nonlinearities is by using the polytopic model approach to reduce the complexity of the automatic control problems. The goal of this chapter is to show the interesting properties of polytopic models as well as their eventual limits. By means of pedagogical examples, this chapter shows how polytopic models can be employed to model nonlinear systems. Stability results are also proposed to design a state feedback controller, and observers for state and unknown input estimations. A fault-tolerant control strategy is also proposed based on an appropriate combination of the state feedback law and the proposed unknown input observer. This strategy is applied to the control of the lateral dynamics of a vehicle in the presence of actuator faults in order to illustrate its validity. A rich survey bibliography is also proposed by the authors.

Polytopic models for observer and fault-tolerant control designs

http://w3.cran.univ-lorraine.fr/perso/benoit.marx/2009_SAFEPROCESS_ORJUELA.pdf

José Ragot

Papers

A new method for determining PCA models for system diagnosis

On the stability analysis of a class of multiple models

Robust fault and state estimation for linear discrete-time systems with unknown disturbances using PI Three-Stage Kalman Filter

Polytopic models for observer and fault-tolerant control designs

Observer design for nonlinear systems described by multiple models