Abstract

Sliding modes in dynamical systems have been historically studied because of their strong robustness properties to a certain class of uncertainty. In feedback control systems, this is achieved by employing nonlinear control/injection signals to force the system trajectories to attain, in finite time, a motion along a surface in the state-space. The associated reduced order dynamics the system exhibits, whilst constrained to the surface, is called the sliding motion. This motion possesses strong robustness properties to so-called matched uncertainty. These nonlinear injection techniques can also be applied to observer problem formulations, and result in intriguing properties.
This talk will consider how sliding mode ideas can be exploited for fault detection (specifically fault signal estimation) and fault tolerant control. In particular the talk will describe how sliding mode observers can be used for fault estimation in dynamic systems by exploiting the `equivalent injection’ signal necessary for maintaining sliding. The talk will attempt to demonstrate the practicality of these methods with examples of applications of these ideas to aerospace systems. This will include results demonstrating the successful real-time implementation of a sliding mode fault tolerant control scheme on a motion flight simulator configured to represent the aircraft associated with the El-AL Bijlmermeer incident.

Biography

Christopher Edwards is Professor of Control Engineering in the College of Engineering, Mathematics and Physical Sciences at the University of Exeter, UK. He began his academic career in the department of Engineering at the University of Leicester as a Lecturer in 1996. He was promoted to Senior Lecturer in 2004, Reader in 2008 and awarded a Personal Chair in 2010, before moving to Exeter in 2012. He is a member of the IEEE and a member of the IMA (which constitutes chartered mathematician status). He is currently a member of the IEEE technical committee on Variable Structure Systems and a subject editor for the International Journal of Robust and Nonlinear Control. In 2006, Christopher Edwards was awarded a Royal Academy of Engineering Senior Research Fellowship. His current research interests are in sliding mode control and observation, and their application to fault detection and fault tolerant control problems. He is the author of over 250 refereed papers in these areas, and two books: Sliding mode control: theory and applications (1998), and Fault Detection and Fault Tolerant Control using Sliding Modes (2011). In addition he recently co-edited the monograph Fault Tolerant Flight Control: a Benchmark Challenge (2010) based on GARTEUR AG16. He has been involved in the recent European FP7 project: 'ADDSAFE' which seeks to study state-of-the-art model based FDD techniques to assist in the 'greening' of aircraft to help reduce fuel consumption and carbon emissions.

Abstract

The study of complex dynamic processes governed by nonlinear and nonstationary characteristics is a problem of great importance in the analysis and control of power system oscillatory behavior. Power system dynamic processes, in particular, are highly random, nonlinear to some extent, and intrinsically nonstationary even over short time intervals as in the case of severe transient oscillations in which switching events and control actions interact in a complex manner. Prediction of temporal dynamics, with the ultimate application to real-time system monitoring, protection and control, remains a major research challenge due to the complexity of the driving dynamic and control processes operating on various temporal scales that can become dynamically involved.
Frequency and damping of measured oscillations may be sensitive indicators of the health or condition of the power system, and provide an early warning system for control actions. By tracking the evolving dynamics of the underlying oscillations, the onset of system instability can be determined and the critical stages for analysis and control can be identified. On the other hand, monitoring the state of the system in real time it is possible to detect the presence, magnitude and extent of operational threats.
This talk discusses the development of health monitoring methods for complex power systems. Detection and accurate identification of temporal variations in the dynamic pattern of system oscillations lies at the heart of developing novel algorithms for instability or threat detection in stressed power systems. The cornerstone to the proposed procedure is a nonlinear time-varying technique that separates a measured signs into a series of amplitude – as well as frequency – modulated signal components directly in near-real time from which frequency and damping can be accurately extracted. This information is then processed to extract the underlying incident energy propagating through the system.
Critical elements that are essential to successful application of robust dynamic health monitoring systems are reviewed and methods to determine the health of the system in near-real time are discussed. Using concepts from the field of damage detection in mechanical systems, deviations in the system dynamics resulting from modifications of system operating conditions are detected by use of an adaptive time-energy-frequency monitoring technique. The multiscale problem is solved by multiscale decomposition of the data over a sliding window based adaptive (statistical) reduction technique.
These methods are capable of identifying small variations in system performance associated with the important goal of detecting incipient instability and performance degradation and are expected to be a step toward developing smart-grid sensors and on-line wide-area control schemes. Distinct from previous approaches, the developed threat monitoring techniques are capable of identifying multiple simultaneous threats – i.e. multiple simultaneous system variations as well as signal features representing abnormal operation. Application examples include actual system measurements from the Mexican power grid.

Biography

Arturo Roman-Messina received the M. Sc. degree (Honors) in Electrical Engineering from the National Polytechnic Institute of Mexico, in 1987, and the Ph. D. degree from Imperial College of Science, Technology & Medicine, London, U. K., in 1991. He has been an academic visitor at Imperial College, London, UK (1997, 2007), Iowa State University, USA (2003-2004) and Arizona State University, USA (2005-2006). Since 1997 he has been a Professor in Electrical Engineering at the Center for Research and Advanced Studies (Cinvestav), Mexico.
Arturo Messina is an active researcher contributing to the advancement of computer-aided design tools and theoretical models for the analysis and control of large-scale power systems. He is the Editor of the book Inter-area Oscillations in Power Systems – A Nonlinear and Non-stationary Perspective, Springer 2009, and is a co-author of several books, monographs and special issues on various aspects of power system monitoring and control.
Currently, he is serving as a member of the editorial board of the journal Electric Power Components and Systems and as an Associate Editor of the IEEE Transactions on Power Systems. He was named IEEE Fellow in 2012 and is the recipient of numerous prestigious awards including the 2011 Doble Knowledge Leadership Award.

Abstract

Diagnosis is the process of identifying or determining the nature and root cause of a failure, problem, or disease from the symptoms arising from selected observations, checks or tests. The different facets of this problem and the wide spectrum of classes of systems and applications make it interesting to several communities and call for bridging several technologies.
In particular, diagnosis must work from the signals that permit efficient fault detection towards the upper levels of supervision that call for qualitative interpretations. Hence the interfaces between continuous signals and their abstract interpretations, in symbolic or event-based form, are essential. To do that, discrete formalisms borrowed from Artificial Intelligence find a natural link with continuous models from the Control community. These two communities have their own diagnosis track:

But there has been a growing number of researchers in both communities, who tried to understand and incorporate approaches from their parallel research fields to build better and more effective diagnostic systems.
Model-based approaches and data-driven approaches based on machine learning techniques are present in both communities and also complement synergically to provide solutions to a variety of diagnostic problems whose difficulty arises from the scarse nature of the instrumentation or, oppositely, from the massive amounts of data to be interpreted for the emergence of hidden knowledge.
Other bridges can be found when considering that diagnosis is not a goal per se but a piece in fault management architectures. It takes part in the solutions produced for tasks such as design, failure-mode-and-effects analysis, sensor placement, on-board recovery, condition monitoring, maintenance, repair and therapy planning, prognosis. The contribution of diagnosis in such architectures means close links with decision tasks such as control and planning and calls for innovative integrations.
This talk will provide a comprehensive picture of the different facets of diagnosis, illustrated by real world problems and exemplify how different technologies can be synergically integrated to provide better solutions for fault management problems.

Biography

Louise Travé-Massuyès is Research Director of the Centre National de la Recherche Scientifique (CNRS), working at Laboratoire d’Analyse et d’Architecture des Systèmes (LAAS), Toulouse, France. She received a Ph.D. degree in control in 1984 and an Engineering Degree specialized in control, electronics and computer science in 1982, both from the Institut National des Sciences Appliquées (INSA) in Toulouse, France; then an Habilitation à Diriger des Recherches from Paul Sabatier University in 1998. Her main research interests are in Dynamic Systems Supervision and Diagnosis with special focus on Qualitative, Model-Based Reasoning methods and data mining. In CNRS-LAAS, she is the head of the Diagnosis and Supervisory Control (DISCO) research team for several years. She has been particularly active in bridging the AI and Control Model-Based Diagnosis methods, as leader of the BRIDGE Task Group of the MONET European Network. She has been responsible for several industrial and european projects and published more than 200 papers in international conference proceedings and scientific journals and one patent. She is member of the IFAC Safeprocess Technical Committee and Senior Member of the IEEE Computer Society.

Abstract

The talk addresses aspects of the problem of reliable/resilient coordination and control of distributed systems over shared infrastructures. This type of systems have sustained tremendous growth rates recently due to the proliferation of digital and networking technologies, and include a variety of sensor/actuator networks, such as electric power distribution systems (e.g., smart grids), robotic networks, and transportation systems of various sorts. More specifically, we consider a distributed system whose components (nodes) can locally exchange information in an iterative fashion via interconnections (edges) that form an arbitrary, possibly directed topology (digraph). We focus on linear iterative updates in which the nodes maintain and update certain values based on linear combinations of their own values and the values they successfully receive from their neighbors. By employing appropriate encoding of the data and/or by taking advantage of redundant paths in the topology of the network, we develop resilient iterative strategies to compute functions (such as the average) of the initial values that the nodes posses, despite unreliable (packet-dropping) links and/or incorrect actions by faulty/malicious nodes. These calculations can be used as primitives for providing resilience to a variety of distributed control, optimization, and coordination tasks.

Biography

Christoforos Hadjicostis is Associate Professor in the Department of Electrical and Computer Engineering at the University of Cyprus. He received S.B. degrees, the M. Eng. degree, and the Ph.D. degree in Electrical Engineering and Computer Science, all from MIT. From 1999 to 2007, he was Assistant and then Associate Professor with the Department of Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign. His research focuses on fault diagnosis and tolerance in distributed dynamic systems; error control coding; monitoring, diagnosis and control of large-scale discrete event systems; and related applications in embedded systems, distributed robotics, anomaly detection and network security, and biomolecular networks. He is the author of a research monograph on "Coding Approaches to Fault Tolerance in Combinational and Dynamic Systems" (Springer, 978-0-7923-7624-8) and the recipient of several awards, including a 2001 NSF Career Award. Christoforos Hadjicostis has served or is serving on the Editorial Boards of IEEE Transactions on Automatic Control, IEEE Transactions on Circuits and Systems (Part I), IEEE Transactions on Control Systems Technology, and International Journal of Discrete Event Dynamic Systems. He currently serves as Vice-Chair for the IFAC Technical Committees on Discrete Event and Hybrid Dynamic Systems and on Stochastic Systems.

Abstract

Most of popular synthesis techniques of fault detection and isolation (FDI) filters (e.g., parity space methods, geometric methods, unknown input observer based methods) can not be considered as satisfactory numerical approaches. The main reasons for this are the lack of generality and/or the lack of numerical reliability. To remedy this situation, a new generation of numerically reliable computational algorithms has been developed by the author in the last decade. The new algorithms are able to solve various FDI synthesis problems in the most general setting, without any technical assumptions. In the development of the new computational techniques two computational paradigms emerged, which are instrumental in developing generally applicable, numerically reliable and computationally efficient synthesis methods. The first paradigm is the use of so-called integrated synthesis algorithms, where the resulting fault detection filters are determined by successive updating of partial syntheses addressing specific requirements. Since each partial synthesis represents a valid fault detection filter, this approach has an increased flexibility in combining different synthesis techniques when compared with the traditionally used one-shot techniques. However, the main strength of the integrated algorithms lies in their ability to exploit at each updating step all available structural information at the previous step, which overall leads to very efficient structure exploiting computations. The second paradigm is the use of the nullspace method as a first synthesis step to simplify and even solve various synthesis problems. The main appeals of the nullspace based fault detection filter synthesis are: generality, being applicable to both standard and singular (or non-proper) systems; numerical reliability, by relying on numerically sound computational techniques; and flexibility, by leading to simplified problem formulations which allow to easily check solvability conditions and address least order synthesis problems. Applications of these paradigms in solving synthesis problems for linear parameter varying systems and linear time-varying periodic systems have been recently done.

Biography

Andreas Varga received the diploma in control engineering in 1974 and the Ph.D. degree in electrical engineering in 1981, both from the University "Politechnica" of Bucharest (Romania). From 1974 to 1993 he has held various research positions at the Institute of Informatics Bucharest and at the Ruhr-University of Bochum. From 1990 to 1992 he worked at the Ruhr-University of Bochum as visiting research fellow in the framework of a fellowship award of the Alexander von Humboldt Foundation. Since 1993, he has been at the German Aerospace Center (DLR) in Oberpfaffenhofen, where he is currently a Senior Scientist. He was a visiting fellow at the Kyoto University (1994), California Institute of Technology (2000), Australian National University (2000), University of Hong Kong (2000), and University of Umea (2002,2008).
Andreas Varga's main research interests include the numerical methods for linear systems analysis and design (with special focus on model and controller reduction, descriptor systems, periodic systems, fault detection), and robust numerical software for computer aided control system design (CACSD). He coauthored three books, coedited two books, published over 60 papers in refereed journals or book chapters, and has over 145 conference publications.
Andreas Varga is Fellow of IEEE and served as Associate Editor for the IEEE Transactions on Automatic Control between 1997-1999. He was the Program Chairman of the 1999 Symposium on CACSD (Hawaii), the General Chair for the 2000 Symposium on CACSD (Anchorage, Alaska), the General Chair of the joint conferences 2006 IEEE Conference on Control Applications, 2006 IEEE Symposium on CACSD and 2006 IEEE International Symposium on Intelligent Control (Munich, Germany). For 2000-2004 he was the Chairman of the Technical Committee on CACSD within the IEEE Control Systems Society and for 2002-2003 he was a nominated member of the Board of Governors of the IEEE Control Systems Society.

Abstract

Modelling, analysis and control of networked control systems (NCS) have recently emerged as topics of significant interest to the control community. The defining feature of any NCS is that information is exchanged using digital band-limited serial communication channel among systems components and usually shared by other feedback control loops. Conventional control theory with many ideal assumptions, such as synchronized control and non-delayed sensing and actuation must be revisited so that the limitations on communication capabilities within the control design framework can be integrated. Furthermore, the new trend is also to implement the realization of fault diagnosis and fault tolerant control systems that employ supervision functionalities and reconfiguration mechanisms by using cooperative functions that are also distributed on a networked architecture.
More recent researches to handle these problems can be divided into two categories, respectively Control of network and Control over network. However, recent achievements showed that it is possible to solve communication problems and control problems simultaneously. Of course, a combination of both approaches contributing to a more efficient NCS design.
This talk intends to provide an introduction to the problems that arise in NCS design and present different co-design approaches. Aim is to present co-design approaches that integrate in a coordinated way fault diagnosis and control performances as well as real-time scheduling constraints. The advantage of this integrated approach is mainly the minimization of the resources necessary for meeting the required Quality of Control. This problem is of a prime importance in embedded applications.

Biography

Dominique Sauter received the Doctorat ès Sciences Degree (1991) from the University Henri Poincaré, Nancy1, France. Since 1993 he is a full Professor at this University, where he teaches Automatic Control. He has been the head of the Electrical Engineering Department during 4 years and Vice-Dean of the Faculty of Sciences and Technology. He is a member of the Research Center in Automatic Control of Nancy (CRAN) associated to the French National Center For Scientific Research (CNRS). His current research interests are focused on model-based fault diagnosis and fault tolerant with emphasis on networked control systems. The results of his research works are published in over 50 articles in journals and book contributions and 150 conference papers. Dominique Sauter is currently serving as an associate editor for the journal of Applied Mathematics and Computer Science and senior editor for the Journal of Intelligent & Robotic Systems. He has also been appointed by The IEEE control system society to the position of general chair for the organisation of the IEEE Multi Conference on system and control 2014 (MSC’14).

Abstract

Vehicle and passenger safety is a critical issue for public authorities as well as for car manufacturers and suppliers. Besides drivers’ training and information many technological advances have been performed since a couple of years and have drastically improved the road safety.
Nevertheless the core problem remains the driver itself. Several studies held both in US and in Europe show that 90% of the accidents are due to intentional or non-intentional behaviors of the drivers, for example a bad perception or knowledge of the environment but also reduced physiological or psychological conditions.
The Vehicle/Driver/Environment process can easily be compared to a closed loop system where the driver plays the role of the management/control unit. The driver pilots the vehicle considering the information it delivers, its perception of the environment and according to the targets and planning that have been set. Furthermore, the driver’s behavior is influenced by its driving aptitude and capacity and should also be disturbed by environmental conditions.
Despite the development of more and more sophisticated Advanced Driver Assistance Systems (ADAS) that substitute the driver in critical situations, it is currently not possible to fully exclude it from the vehicle management loop. Furthermore, the deployment of ADAS will really be efficient and accepted since it will fit with driver’s needs, aptitudes and capacities to deal with complex environmental contexts, but also when providing an adapted assistance through a human centered design.
Thus, an important issue is to get a better on-line knowledge about the driver and its limitations. Within this context, original functions providing an on-line driver state diagnostic about sleepiness and visual or cognitive distraction have been studied. These works are including the design and the development of complete systems from the measurement settings, up to the Human Machine Interaction concepts. A special effort was dedicated to design reliable driver’s diagnostic processes. As the managed information is often imprecise or uncertain the use of qualitative reasoning methods has been foreseen. Finally, these functions and systems have been successfully implemented on several experimental vehicles and evaluated in real driving conditions.

Biography

Serge Boverie received his Electrical Engineering degree and DEA in Control Engineering from INSA in 1979 and a PhD in Automatic Control in Toulouse, 1981. In 2011, he was awarded a Habilitation (HDR) in Computing science control engineering and signal processing. In 1987, he joined the Siemens VDO Automotive SAS, now Continental Automotive France S.A.S., in Toulouse. Since 2002, he is head of the department of advanced development for safety applications and he is also acting as Principal Expert. His domains of interest include Perception Systems, Human Machine Interaction, Advanced Driver Assistance Systems (ADAS) and Human Monitoring. He is the author and co-author of 10 patents, of more than 90 papers published in international conferences, scientific journals and of one book dedicated to the applications of fuzzy control. From 1993 to 2002, he was editor for the CEP journal. Since 1992, he has been involved in the IFAC organization acting as Vice Chairman then Chairman of "Component and Instrument" Technical Committee (1993- 2005), then as Chairman of the Mechatronics, Robotics and Components Coordinating Committee (2005-2008). From 2008 to 2014 he is Vice-chair of the Technical Board until France will take the presidency of the IFAC organization where he will be in charge of the Industrial Vice Chair. In 1993 he received the IFAC Congress Applications Price; in 2001 the Science Award from the French Ministry of research (PREDIT program); in 2005 the IFAC Award for Industrial Achievement; in 2007 the French Award for his implication in IFAC organization, and in 2005 and 2008 the IFAC Outstanding Awards.