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.

Robust control design based on parametric eigenvalue assignment

Abstract: Optimal robust control design of multivariate systems using eigenstructure assignment is addressed. An analytical parametric expression of state-feedback eigenstructure assignment is derived for both real and complex-conjugate eigenvalues. The controller designed via state-feedback eigenstructure assignment is analytically expressed by new totally free parameters for the case where the sets of closed- and open-loop eigenvalues intersect, and the case where those do not. It considers both the desired closed-loop eigenvalue assignment in the time domain and the minimization of the mixed performance and robustness index in the frequency domain so that the frequency- and time-domain performance specifications are combined during the controller design. The gradient calculation of the mixed performance and robustness index is described in detail. Based on gradient-based optimization and genetic algorithms, the mixed performance and robustness index is minimized by making full use of the freedom provided by eige...

Decentralized fault estimation and fault-tolerant control for large-scale interconnected systems: An integrated design approach

Abstract: A large-scale interconnected system consists of large numbers of coupled subsystems. This coupling gives rise an important problem of integrating the designs of fault estimation (FE) and fault-tolerant control (FTC) in the presence of unexpected faults. This paper proposes an integrated FE/FTC design for large-scale interconnected systems with uncertain nonlinear interactions and unknown bounded actuator faults. A decentralized FTC controller is developed to guarantee the robust stability of the overall interconnected system, using the state/fault estimates obtained simultaneously by a decentralized unknown input observer. The observer and controller gains are solved simultaneously using a single-step linear matrix inequality (LMI) formulation. The performance effectiveness of the proposed design is demonstrated by applying it to the stabilization of a 3-machine power system.

Optimal Eigenstructure Assignment for Multiple Design Objectives

Abstract: This paper considers the application of eigenstructure assignment in the design of multi-criteria controllers with a gradient-based numerical optimization procedure using analytically derived gradients. Emphasis is placed on the design of output feedback control laws which possess certain additional desirable properties. By allowing the closed-loop eigenvalues to be selected (where appropriate) from regions of the complex plane extra design freedom is introduced which may be used to achieve, for example, robust eigenvalue assignments and a low norm control law more easily.

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