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.

Monte Carlo Analysis of Bayesian Optimization-based Pitch Controller with Pitch Fault Compensation for Offshore Wind Turbine

Abstract: Offshore wind turbine (WT) rotors are subjected to asymmetrical loads, resulting in enhanced fatigue of the blade structures, which requires reliable load mitigation techniques (e.g. individual pitch control, IPC). The IPC-enhanced pitch motion increases the occurrence of pitch actuator faults. This phenomenon has accelerated the emergence of new research areas combining IPC with the fault tolerant control (FTC)-based fault compensation. The research considering the IPC and pitch system-related FTC is referred to as a fault-tolerant IPC “co-design” scheme. However, it is important to enhance the robustness of this scheme by careful design of the IPC system. The robustness is tuned using a Bayesian optimization-based Proportional-Integral PI control. The Bayesian optimization algorithm is adopted to search for optimal controller coefficients by evaluating the Gaussian process model between the designed objective function and the coefficients. The pitch actuator faults are estimated and compensated by the robust unknown input observer UIO-based FTC strategy. The robustness and effectiveness of this “co-design” scheme are verified using the 5MW NREL FAST WT with Monte Carlo simulations.

The Design and Assessment of a Sliding Mode Controller for the Lateral Motion Model of an Aircraft

Abstract: The design of a multivariable sliding mode controller for an unmanned aircraft is described and an emphasis on robust eigenstructure assignment is given. The linear and non-linear model responses are compared when subjected to the same variable structure control design. It is shown that, after sliding has commenced the response of the objective system is tracked by the corresponding nonlinear system. A measure of sensitivity is defined as the proximity of a sub-space of the actual system response from the designed objective.

On Eigenvectors and Generalized Eigenvectors in Multi-Variable Descriptor Control Systems

Abstract: This paper is concerned with an eigenvector problem in multi-variable descriptor control systems. It proves that the eigenvectors and generalized eigenvectors premultiplied by the singular matrix E of the descriptor system as well as the eigenvectors and the generalized eigenvectors, which play a very important role in the design of multi-variable descriptor systems via eigenstructure assignment, are linearly independent.

Robust LPV Estimator Approach to Friction Diagnosis

Abstract: The control of systems that involve friction presents interesting challenges. Recent research has focused on detailed modelling of friction phenomena as a very complex and difficult modelling challenge. However, the friction effects acting in a dynamic system can be viewed as actuator faults with time-varying characteristics to be estimated and compensated within a Fault Detection and Diagnosis (FDD) scheme, so that the limitations arising from the use a friction model are obviated. This work is motivated by the utilisation of robust Linear Parameter Varying (LPV) estimation approach providing effective and robust fault estimation. The approach is illustrated using a two-link manipulator system with Stribeck friction. Results show that the time-varying friction forces on each joint can be simultaneously and robustly estimated through the online measurement of the varying parameters.

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