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.

Rapid prototyping of a sensor fault tolerant traction control system

Abstract: The problem of sensor faults on an AC-drive system for an electric train is considered. Intermittent disconnections of these sensors produces severe transient errors in the estimator in the control loop if not heavily filtered to suppress these errors which will degrade performance. This paper shows that model based techniques can be applied for achieving reliable tolerance of intermittent disconnections without degrading performance. A bilinear model of the motor is used to produce a fault tolerant scheme for estimation of control variables. This paper goes beyond simulation to show how such a system can be verified in hardware. A small test-rig is built with a DSP used to run fault tolerant scheme.

Phase modulation of robust variable structure control for nonlinear aircraft

Abstract: This paper concerns phase plane description and modulation of the performance for a nonlinear Unmanned Aerial Vehicle (UAV) system based on Variable Structure Control (VSC) by reaching sliding mode. The novelty lies in the application of a phase analysis approach to achieve a robust controller for a complex nonlinear system. The aircraft dynamics are introduced and approximately linearized and decoupled on-line using feedback linearization theory. Then the sliding mode control (SMC) scheme is accomplished for the decoupled sub-channels. The phase modulation method is applied for theoretically ensuring further robustness. The simulation results demonstrate the efficiency and effectiveness of the proposed strategy.

Fault diagnosis using quantitative and qualitative knowledge integration

Abstract: This paper presents a novel approach to integrating quantitative and qualitative information in fault-diagnosis, and which is based on the use of associative B-spline functions. The underlying concept is to structure an artificial neural network which can model highly nonlinear systems efficiently, in a fuzzy logic format. The network could therefore be trained more rapidly and will also provide a linguistic description about the causes of faults. The diagnosis approach is put to the test through a digital simulation study of a nonlinear two-tank system.

Fault-tolerant control systems design using the linear matrix inequality method

Abstract: This paper discusses an approach to robust control law design for fault-tolerant systems. Based on the assumption that the effects of faults can be expressed in Linear-Fractional-Transformation (LFT) forms, a fault-tolerant control systems design problem is formulated and solved via a linear matrix inequality (LMI)-based synthesis approach, to recover the convexity of the design problem whilst considering the robust performance and robust stability against faults and uncertainties simultaneously, a constrained optimisation approach is used. The simulation results of a design example (a longitudinal motion flight control problem for an unmanned aircraft in the case of suffering battle damage on its wing) shows that the robust stability and satisfactory performance are achievable.

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