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

This paper discusses conditions on stability and stabilization of continuous Takagi-Sugeno (T-S) systems. Stability analysis is derived via nonquadratic Lyapunov function method and LMIs (Linear Matrix Inequalities) formulation. The nonquadratic Lyapunov function is built by inference of quadratic Lyapunov function on the same basis as the T-S model itself. We show that stability condition of the open-loop T-S systems is assured under certain restrictions on the rate of change of state variables. Following a similar approach, stabilization of the closed-loop continuous T-S systems using the well-known PDC (Parallel Distributed Compensation) technique is investigated. The design methodology is illustrated by numerical examples.

Stability analysis and design for continuous-time Takagi-Sugeno control systems

In this paper, the separation principle for discrete nonlinear systems in multiple model representation is investigated. The separation principle deals with a property which allows the multiple observer and the multiple controller to be designed separately. Using the quadratic Lyapunov technique and LMIs (Linear Matrix Inequalities) formulation, sufficient conditions for the global exponential stability of discrete multiple controllers are derived which are dual to those for the global exponential convergence of discrete multiple observers. A numerical example is given to illustrate the method.

Output stabilisation in multiple model approach to modelling

This paper addresses the problem of state estimation of nonlinear systems described by a Takagi-Sugeno multiple model with unmeasurable decision variables. The method is based on the reformulation of the multiple model in an equivalent form. First, the convergence conditions of the state estimation error are established using the Lyapunov method and they are expressed in LMI formulation. Secondly, performances of the observer are enhanced by pole clustering and L 2 attenuation of bounded exogenous disturbances. Finally, the method is applied to estimate the state of a link flexible joint robot.

/pdf/state-estimation-of-nonlinear-systems-using-multiple-model-ay8t11fdn9.pdf

State estimation of nonlinear systems using multiple model approach

In this paper, a new method for determining the Principal Component Analysis (PCA) model structure for system diagnosis is proposed. This method, based on the variables reconstruction principle, determines the PCA model optimizing detection and isolation of single or multiple faults affecting redundant or non redundant variables of a system. This new method has been validated by a simulation example.

Determination of principal component analysis models for sensor fault detection and isolation

The paper addresses a systematic procedure to deal with state and parameter uncertainty estimation for nonlinear time-varying systems. A robust observer with respect to states, inputs and perturbations is designed, using a Takagi–Sugeno (T–S) approach with unknown premise variables. Tools of the linear automatic to the nonlinear systems are applied, using the Linear Matrix Inequalities optimization. The observer estimates the uncertainties, the states and minimizes the effect of external disturbances on the estimation error. The uncertainties are modelled in a polynomial way which allows considering the uncertainty estimation as a fault detection problem. The residual sensitivity to faults while maintaining robustness according to a noise signal is handled by H ∞ / H − approach. The method performance is illustrated using the three-tank system.

José Ragot

Papers

Stability analysis and design for continuous-time Takagi-Sugeno control systems

Output stabilisation in multiple model approach to modelling

State estimation of nonlinear systems using multiple model approach

Determination of principal component analysis models for sensor fault detection and isolation

Parameter estimation for uncertain systems based on fault diagnosis using Takagi–Sugeno model