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.

Comparison of fuzzy modelling approaches for fault detection systems

Abstract: Fuzzy modelling together with Parallel Distributed Compensation (PDC)-based system analysis and controller/observer design techniques have emerged among the methods for developing fault detection and isolation (FDI). This paper provides a comparison of fuzzy logic modelling approaches for FDI of complex systems. The work is motivated by the modelling issues of the Takagi-Sugeno (T-S) fuzzy inference operator-based approximation structure that is essential for the implementation of a PDC system. The paper focuses on an application study of fault diagnosis for an industrial actuator system, conducted within the framework of the European study DAMADICS.

Design and evaluation of FTFC scheme for sensor loss detection based on RECOVER benchmark

Abstract: The work proposes a study on fault tolerant flight control of the GARTEUR RECOVER benchmark aircraft model. Instead of using control surface failure scenarios, a sensor loss detection scenario is defined in this benchmark for the first time, to demonstrate the proposed fault tolerant flight control capability. Therefore, the model-based fault tolerant flight control is well posed for this failure scenario, which is different from traditional sensor failure schemes relying on sensor redundancy and consolidation detection. The proposed fault tolerant flight control scheme is simulated and evaluated in various testing manoeuvres during a landing process. In this scheme, a fault estimator based upon ℋ-/ℋ∞ robustness index is utilised to estimate the loss detection. A sensor fault compensator is also included to restore the fault-free sensor measurement on-line.

Insensitive and robust control design via output feedback eigenstructure assignment

Abstract: Insensitive and robust control design using output-feedback eigenstructure assignment for linear multivariable systems is considered in this paper. A parametric expression of closed-loop eigenvectors and generalized eigenvectors is developed. It can cope with the case where the closed-loop eigenvalues are multiple and/or the same as the open-loop ones so that the system to be designed can be uncontrollable and/or unobservable. The controller designed via output-feedback eigenstructure assignment is expressed by proposed parameter vectors. The freedom provided by output-feedback eigenstructure assignment is used to optimize some performance functions which are used to measure the sensitivity of the closed-loop matrix and the robustness of the closed-loop system. Copyright © 2000 John Wiley & Sons, Ltd.

Phenomenological investigation of a distributed parameter model for coordinating the mechanical activity of the mammalian gut

Abstract: Spontaneous electrical rhythms recorded from the gastro-intestinal tract of humans and animals have been modelled using arrays of coupled relaxation oscillators. For the small intestine a one-dimensional chain of coupled van der Pol oscillators has successfully reproduced known physiological data. Recently, the oscillator dynamics have been modelled using modified Hodgkin-Huxley type equations which more closely relate to the ionic activity of smooth muscle. In this paper a distributed formulation of these auto rhythmic equations is solved using a differential quadrature method and results for the case equivalent to 30 coupled oscillators are presented.

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