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

Disturbance-observer-based control (DOBC) and related methods have been researched and applied in various industrial sectors in the last four decades. This survey, at first time, gives a systematic and comprehensive tutorial and summary on the existing disturbance/uncertainty estimation and attenuation techniques, most notably, DOBC, active disturbance rejection control, disturbance accommodation control, and composite hierarchical antidisturbance control. In all of these methods, disturbance and uncertainty are, in general, lumped together, and an observation mechanism is employed to estimate the total disturbance. This paper first reviews a number of widely used linear and nonlinear disturbance/uncertainty estimation techniques and then discusses and compares various compensation techniques and the procedures of integrating disturbance/uncertainty compensation with a (predesigned) linear/nonlinear controller. It also provides concise tutorials of the main methods in this area with clear descriptions of their features. The application of this group of methods in various industrial sections is reviewed, with emphasis on the commercialization of some algorithms. The survey is ended with the discussion of future directions.

/pdf/disturbance-observer-based-control-and-related-methods-an-795w6vym5o.pdf

Disturbance-Observer-Based Control and Related Methods—An Overview

Fault detection, isolation, and reconfiguration (FDIR) is an important and challenging problem in many engineering applications and continues to be an active area of research in the control community. This paper presents a survey of the various model-based FDIR methods developed in the last decade. In the paper, the FDIR problem is divided into the fault detection and isolation (FDI) step, and the controller reconfiguration step. For FDI, we discuss various model-based techniques to generate residuals that are robust to noise, unknown disturbance, and model uncertainties, as well as various statistical techniques of testing the residuals for abrupt changes (or faults). We then discuss various techniques of implementing reconfigurable control strategy in response to faults.

A Survey of Fault Detection, Isolation, and Reconfiguration Methods

Sliding mode observers for fault detection and isolation

Observer-based fault detection and isolation: robustness and applications

Fault detection filters are a special class of observers that can generate directional residuals for the purpose of fault isolation. This paper proposes a new approach to design robust (in the disturbance de-coupling sense) fault detection filters which ensure that the residual vector, generated by this filter, has both robust and directional properties. This is done by combining the unknown input observer and fault detection filter principles. The paper proposes a new full-order unknown input observer, and gives necessary and sufficient conditions for its existence. After the disturbance de-coupling conditions are satisfied, the remaining design freedom can be used to make the residual have the directional property, based on the fault detection filter principle. A nonlinear jet engine system is used to illustrate the robust fault isolation approach presented. It is shown that linearization errors can be approximately treated as unknown disturbances and be de-coupled in the design of a robust fault detect...

Design of unknown input observers and robust fault detection filters

A simple and effective algorithm is derived for estimating abrupt parameter changes by using a combination of detection theory and a Kalman filter algorithm. Simulation results show its excellent ability for tracking sudden parameter changes, and show that the estimates of unchanged parameters are not influenced by the tracking of the changed parameter. The disadvantages of the method, shared with other algorithms for the same purpose, may be a delay of several steps in detecting several parameter changes, and the possibility of false alarm or failure in detecting a change. The estimation may be beneficial when the associated delay is acceptable. >

A recursive identification algorithm for estimating abrupt parameter changes

In this chapter, navigation systems that comprise onboard inertial measurements with external aids, such as Global Positioning System (GPS) or Doppler radar, are considered. The objective of such systems is to reliably estimate the navigation states, which include the position and velocity of the vehicle, from the inertial measurements and the external aids despite the possible occurrence of faults in the inertial measurement unit (IMU) or in the external measurements. Approaches are reviewed for detecting and isolating faults in strapdown inertial measurements, for combining the estimates of the navigation states from subsystems that each use only a subset of the available external measurements, and for detecting the presence of a fault in the external measurement data and avoiding its use in constructing a global navigation state estimate. Finally, a fault-tolerant, integrated navigation system (INS) architecture is suggested which produces a global estimate of the navigation states from two aided navigation subsystems, one combining inertial data with GPS data, and the other combining inertial data with Doppler radar data, which can tolerate IMU faults, one GPS fault, and one Doppler radar fault. Simulation results for one particular mission with selected faults included demonstrate that the suggested architecture is tolerant of these faults in the sense that the navigation state estimates are unaffected.

Hong-Yue Zhang

Papers

Design of unknown input observers and robust fault detection filters

A recursive identification algorithm for estimating abrupt parameter changes

A Study on Fault-Tolerant Integrated Navigation Systems