Ron J. Patton

Bio: Ron J. Patton is an academic researcher from University of Hull. The author has contributed to research in topics: Fault detection and isolation & Robustness (computer science). The author has an hindex of 57, co-authored 351 publications receiving 19210 citations. Previous affiliations of Ron J. Patton include Universities UK & York University.

Identification and fault diagnosis of an industrial gas turbine prototype model

Abstract: This paper addresses a model-based procedure exploiting analytical redundancy for the detection and isolation of faults of a power plant. The residual generation is performed by means of output observers and Kalman filters in connection with the uncertainty affecting the measurements acquired from the monitored system. The model of the process under investigation required to design observers and filters is obtained by identification. The proposed fault detection and isolation tool has been tested on a simulated model of an industrial gas turbine prototype.

Fault diagnosis of the 3 tank system using fuzzy multiple inference modelling

Abstract: This paper proposes a new approach for detecting and isolating faults in a non-linear dynamic process using the multiple model approach. The necessary conditions for the assignability of eigenvalues to a region in the s-plane and the necessary conditions to guarantee the stability of fuzzy models for Takagi-Sugeno (T-S) fuzzy observers are derived. The paper is structured in two stages. The first is to generate residual signals based on a comparison between the actual and estimated states and in the second stage the Takagi-Sugeno fuzzy observer is reconfigured to identify not only the faults but also the degree or severity of each fault. The techniques developed are demonstrated using a laboratory three tank system.

Fault-tolerance as a key Requirement for the Control of Modern Systems

Abstract: : Networks of Embedded Systems are becoming ubiquitous today. The performance of these networks is measured in terms of the Quality of Service (QoS) delivered. This has been taken on board by the Computer Scientists, who have developed concepts like “Ubiquitous” and “Pervasive” Computing. In the world of Control, there has always been an “implicit” QoS, in that the quality or level of performance has been measured using a cost function, often the error between the reference signals and the system outputs. However, such “point-to-point” notions of QoS are fast becoming redundant in the networked, information-rich world. This paper outlines a new way of formulating the Control problem which is suitable for the networked world, enabling Fault Tolerance to become a natural consequence to ensure that the system performance is maintained under all eventualities. Thus Control has to become more ubiquitous, pervasive, and intelligent. To facilitate this outcome, this paper proposes a new research direction which could be termed “Embedded Cognitive Control”, bringing together the various fields of Cognitive Science, Embedded Systems, and Control.

Robust eigenstructure assignment for descriptor systems

Abstract: The robust control design of descriptor systems using eigenstructure assignment is presented. It considers both the desired closed-loop eigenvalue assignment in the time domain and the minimization of a robustness index in the frequency domain, so that the time- and frequency-domain performance specifications are combined in the controller design. An explicit parametric solution for eigenstructure assignment for multivariate descriptor systems is derived by considering both analytical expression and numerical computation. It is also shown that the state feedback controller can explicitly be expressed by free parameters for the case where the sets of closed- and open-loop eigenvalues intersect and the case where they do not. This controller form provides a very useful parametric formulation for optimal robust control design. The gradient calculation of the robustness index with respect to the free parameters is described in detail. The robustness index is minimized by making full use of the freedom provide...

Detection of abrupt changes: theory and application

Abstract: This book is downloadable from http://www.irisa.fr/sisthem/kniga/. Many monitoring problems can be stated as the problem of detecting a change in the parameters of a static or dynamic stochastic system. The main goal of this book is to describe a unified framework for the design and the performance analysis of the algorithms for solving these change detection problems. Also the book contains the key mathematical background necessary for this purpose. Finally links with the analytical redundancy approach to fault detection in linear systems are established. We call abrupt change any change in the parameters of the system that occurs either instantaneously or at least very fast with respect to the sampling period of the measurements. Abrupt changes by no means refer to changes with large magnitude; on the contrary, in most applications the main problem is to detect small changes. Moreover, in some applications, the early warning of small - and not necessarily fast - changes is of crucial interest in order to avoid the economic or even catastrophic consequences that can result from an accumulation of such small changes. For example, small faults arising in the sensors of a navigation system can result, through the underlying integration, in serious errors in the estimated position of the plane. Another example is the early warning of small deviations from the normal operating conditions of an industrial process. The early detection of slight changes in the state of the process allows to plan in a more adequate manner the periods during which the process should be inspected and possibly repaired, and thus to reduce the exploitation costs.

Robust Model-Based Fault Diagnosis for Dynamic Systems

Abstract: 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