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Ron J. Patton

Other affiliations: Universities UK, York University, University of York  ...read more
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.


Papers
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Journal ArticleDOI
TL;DR: A simple algorithm in sequential order is obtained for solution to the problem of robust pole assignment in descriptor linear systems via proportional plus partial derivative state feedback.
Abstract: The problem of eigenvalue assignment with minimum sensitivity in multivariable descriptor linear systems via proportional plus partial derivative state feedback is considered. Different from the purely proportional state feedback case, the number of finite closed-loop eigenvalues is required to be equal to the system dimension. Based on a result in the perturbation theory of generalized eigenvalue problem of matrix pairs, the closed-loop eigenvalue sensitivity measures in terms of the closed-loop normalized right and left eigenvectors are established. By combining these measures and a recently proposed general parametric eigenstructure assignment result for descriptor linear systems via proportional plus derivative state feedback, the robust pole assignment problem is converted into an independent minimization problem. A simple algorithm in sequential order is obtained for solution to the problem of robust pole assignment in descriptor linear systems via proportional plus partial derivative state feedback...

41 citations

Proceedings ArticleDOI
01 Dec 2009
TL;DR: A new approach to fault compensation for FTC is proposed using fault estimation by which the faults acting in a dynamical system are estimated and compensated within an adaptive control scheme with required stability and performance robustness.
Abstract: Faults or process failures may drastically change system behaviour leading to performance degradation and instability. The reliability and fault-tolerance of a control system can be achieved through the design of either an active or passive Fault Tolerant Control (FTC) scheme. This paper proposes a new approach to fault compensation for FTC using fault estimation by which the faults acting in a dynamical system are estimated and compensated within an adaptive control scheme with required stability and performance robustness. The FTC scheme has an augmented state observer (ASO) in the control system, which has an intrinsic robustness in terms of the stability and performance of the estimation error. The design concepts are illustrated using the notion that the friction forces in a mechanical system can be estimated and compensated to give good control performance and stability. The example given is that of a non-linear inverted pendulum with Stribeck friction.

41 citations

Proceedings ArticleDOI
01 Jul 1997
TL;DR: In this paper, the duality between the H ∞ control and estimation problems is established in a straightforward manner, and a linear matrix inequality solution to the estimation problem is introduced to improve the robustness of the fault detection observer.
Abstract: The duality between the H ∞ control and estimation problems is established in a straightforward manner A linear matrix inequality solution to the H ∞ estimation is introduced The freedom contained in the H ∞ estimation solution is used to improve the robustness of the H ∞ fault detection observer

40 citations

Journal ArticleDOI
TL;DR: In this paper, three approaches are proposed to estimate the excitation force from wave elevation, measurement of pressure, acceleration, and displacement, and observing the force via an unknown input observer.

40 citations

Journal ArticleDOI
TL;DR: The main objective of this paper is to expound the singular-value-decomposition (SVD)-based reduction technique proposed to single-input-single-output Takagi-Sugeno (TS) fuzzy models to multivariable cases.
Abstract: The main objective of this paper is to expound the singular-value-decomposition (SVD)-based reduction technique proposed to single-input-single-output Takagi-Sugeno (TS) fuzzy models to multivariable cases. The use of higher order singular value decomposition is proposed in this paper for the complexity reduction of multiple-input-single-output TS fuzzy model approximation. A detailed illustrative example of a nonlinear dynamic model is also discussed.

40 citations


Cited by
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Journal ArticleDOI
TL;DR: This historical survey compactly summarizes relevant work, much of it from the previous millennium, review deep supervised learning, unsupervised learning, reinforcement learning & evolutionary computation, and indirect search for short programs encoding deep and large networks.

14,635 citations

Journal ArticleDOI
TL;DR: This paper attempts to summarise and review the recent research and developments in diagnostics and prognostics of mechanical systems implementing CBM with emphasis on models, algorithms and technologies for data processing and maintenance decision-making.

3,848 citations

Journal ArticleDOI
TL;DR: A unified framework for the design and the performance analysis of the algorithms for solving change detection problems and links with the analytical redundancy approach to fault detection in linear systems are established.
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.

3,830 citations

Book
27 Sep 2011
TL;DR: 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.
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

3,826 citations

Journal ArticleDOI
TL;DR: In this article, the authors review the state of the art of fault detection and isolation in automatic processes using analytical redundancy, and present some new results with emphasis on the latest attempts to achieve robustness with respect to modelling errors.

3,313 citations