Paul M. Frank

Bio: Paul M. Frank is an academic researcher from University of Duisburg. The author has contributed to research in topics: Fault detection and isolation & Robustness (computer science). The author has an hindex of 48, co-authored 228 publications receiving 15777 citations. Previous affiliations of Paul M. Frank include University of Duisburg-Essen & Centre national de la recherche scientifique.

Enhancement of robustness in observer-based fault detection†

Abstract: A prerequisite for the feasibility of the technique of observer-based fault detection and isolation (FDI) in dynamic systems is a satisfactory robustness with respect to modelling uncertainties. This paper surveys the most relevant methods to increase the robustness in both the stage of residual generation and residual evaluation. Among these methods are the generalized observer scheme, the robust parity space check, the unknown input and H ∞ observer scheme, the decorrelation filter, and the concept of adaptive threshold selection. It is pointed out that the unknown input observer concept, which provides perfect decoupling from the modelling errors or its optimal approximation with the aid of H ∞ techniques, constitutes a general framework of robust residual generation that generalizes and unifies numerous other approaches, among them the parity space and detection filter approach. It is further shown that this FDI method can even be applied to a certain class of nonlinear systems.

Robust H/sub /spl infin// disturbance attenuation for a class of uncertain discrete-time fuzzy systems

Abstract: The paper is concerned with robust stabilization and H/sub /spl infin// control of a class of uncertain discrete-time fuzzy systems. The class of uncertain systems is described by state space Takagi-Sugeno (TS) fuzzy models with linear nominal parts and norm-bounded parameter uncertainties in the state and output equations. First, a sufficient condition on robust stability of the fuzzy models is proposed. Then, H/sub /spl infin//-disturbance attenuation performance of the fuzzy models is analyzed. Some sufficient conditions are derived on robust H/sub /spl infin//-disturbance attenuation in which both robust stability and a prescribed H/sub /spl infin// performance are required to be achieved, irrespective of the uncertainties. A numerical example shows the use of the results on the stabilization and H/sub /spl infin//-disturbance attenuation of a class of discrete-time nonlinear systems via fuzzy switch.

Strong tracking filtering of nonlinear time-varying stochastic systems with coloured noise: application to parameter estimation and empirical robustness analysis

Abstract: The strong tracking filter (STF) proposed by Zhou et al. in 1992, which was developed for nonlinear systems with white noise, is extended to a class of nonlinear time-varying stochastic systems with coloured noise. A new concept of‘softening factor’is introduced to make the state estimator much smoother; its value can be preselected by computer simulations via a heuristic searching scheme. The STF is then used to estimate the parameters of a class of nonlinear time-varying stochastic systems in the presence of coloured noise. The robustness against model uncertainty of the STF is thoroughly studied via Monte Carlo simulations. The results show that the STF has strong robustness against model-plant parameter mismatches in the statistics of the initial conditions, the statistics of the process noise and the measurement noise, the system parameters, and the parameters in the measurement noise model. To a great extent the STF can give bias-free parameter estimations, where the parameters may be randomly time ...

Evolutionary algorithms for solving multi-objective problems

Abstract: List of Figures. List of Tables. Preface. Foreword. 1. Basic Concepts. 2. Evolutionary Algorithm MOP Approaches. 3. MOEA Test Suites. 4. MOEA Testing and Analysis. 5. MOEA Theory and Issues. 3. MOEA Theoretical Issues. 6. Applications. 7. MOEA Parallelization. 8. Multi-Criteria Decision Making. 9. Special Topics. 10. Epilog. Appendix A: MOEA Classification and Technique Analysis. Appendix B: MOPs in the Literature. Appendix C: Ptrue & PFtrue for Selected Numeric MOPs. Appendix D: Ptrue & PFtrue for Side-Constrained MOPs. Appendix E: MOEA Software Availability. Appendix F: MOEA-Related Information. Index. References.

Stability of Time-Delay Systems

Abstract: Preface, Notations 1.Introduction to Time-Delay Systems I.Frequency-Domain Approach 2.Systems with Commensurate Delays 3.Systems withIncommensurate Delays 4.Robust Stability Analysis II.Time Domain Approach 5.Systems with Single Delay 6.Robust Stability Analysis 7.Systems with Multiple and Distributed Delays III.Input-Output Approach 8.Input-output stability A.Matrix Facts B.LMI and Quadratic Integral Inequalities Bibliography Index

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