On fractional derivatives and systems
Manuel Duarte Ortigueira
Electrical Engineering Department of the Faculty of Science and Technology of Universidade Nova de Lisboa.
Abstract: Fractional behavior is ubiquitous. In fact, many natural and man-made systems exhibit a fractional behavior that can be observed from several representations. The most important are the “power law”, the “long range dependence”, and the “non 20-dB increase/decrease” in Bode diagrams. This will be illustrated with some examples.
To obtain correct mathematical formulations for modelling such systems, the fractional derivatives are required. In order to avoid the difficulty of introducing many derivative formulations, a heuristic approach will be followed in order to obtain derivatives with a full agreement with classic results that will emerge as particular cases.
The fractional linear systems will be presented and a brief study will be done.
Biography: Manuel Duarte Ortigueira graduated in Electrical Engineering at Instituto Superior Técnico, Universidade Técnica de Lisboa, April 1975 and got the PhD and Habilitation degrees at the same Institution in 1984 and 1991, respectively. Nowadays he is Associate Professor with Habilitation at the Electrical Engineering Department of the Faculty of Science and Technology of Universidade Nova de Lisboa. He was professor at Instituto Superior Técnico and Escola Náutica Infante D. Henrique. He published 2 books on Digital Signal Processing and on Fractional Calculus, 3 integral texts for 3 courses and other 7 texts corresponding to several themes of different courses, and over 130 papers in journals and conferences, mainly on Fractional Signal Processing. His research activity started in 1977 at Centro de Análise e Processamento de Sinais, continued at Instituto de Engenharia de Sistemas e Computadores (INESC), where he was with the Digital Signal Processing and Signal Processing Systems groups, and since 1997, at Instituto de Novas Tecnologias (UNINOVA), where he is with the Telecommunications and Signal Processing group of Centre of Technology and Systems. He is regular reviewer of several international journals and member of the scientific committee of international journals and conferences. Nowadays his main scientific interests are: Fractional Signal Processing, Digital Signal Processing and Biomedical Signal Processing.
What Authors Should Know to Successfully Publish Papers in Good Journals
Department of Electrical and Computer Engineering University of Louisville, Louisville, Kentucky 40292, USA.
Abstract: Since different publication formats are designed to reach various audiences, they often undergo different review procedures, and have widely different impact. Ultimately, however, papers and publications are judged by their relevance, readership and citations they acquire. Bibliometric impact measures for journals and for individuals as expressed by Impact Factor and other indicators are reviewed and compared for major journals in different subject areas. Forward citation trees provided by ISI/Web of Science are reviewed as ultimate examples of authors’ achievement. Open Access publishing paradigm is also discussed. By comparing the perspectives of authors, readers and editors, this seminar offers ample guidelines for reviewing, but mostly for preparing, writing and publishing successful technical papers. Practical guidance for authors is also covered as well as ethical aspects of publishing.
Biography: Dr. Jacek Zurada serves as a Professor with the Electrical and Computer Engineering Department at the University of Louisville, Kentucky. He was Department Chair from 2004 to 2006. He has published 380 journal and conference papers. He also has authored or co-authored three books and co-edited a number of volumes in Springer Lecture Notes in Computer Science. His research interests cover data mining with emphasis on data and feature understanding, deep and constrained learning of features, rule extraction from semantic and visual information, machine learning, decomposition methods for salient feature extraction, neural networks, and support vector machines.
His original research discoveries include the lambda learning rule of a neuron (referred to by some authors as ‘Zurada learning rule’), a technique for salient feature detection in neural network models, an algorithm for drug dosing prediction, constrained learning of autoencoders with non-negative weights, methods of extraction of logic rules from data based on decision trees (with experiments including bioinformatics data and secondary protein structure prediction, and text data such as newsgroups), extension of complex-valued neurons to associative memories and perceptron networks, and the invention of the dynamic switching hysteresis and switching margins for fast VLSI logic circuitry. His work was cited over 9200 times.
He has held visiting appointments at Princeton, Northeastern, Auburn, and overseas in Australia, Chile, China, France, Germany, Hong Kong, Italy, Japan, Poland, Singapore, Spain, South Africa and Taiwan. Dr. Zurada was an Associate Editor of IEEE Transactions on Circuits and Systems, Pt. I and Pt. II, and served on the Editorial Board of the Proceedings of IEEE. From 1998 to 2003 he was the Editor-in-Chief of IEEE Transactions on Neural Networks. He is an Associate Editor of Neurocomputing, Schedae Informaticae, International Journal of Applied Mathematics and Computer Science, Advisory Editor of Int’l Journal of Information Technology and Intelligent Computing, and Editor of Springer Natural Computing Book Series.
He has served the profession in various capacities, as 2014 IEEE VP-Technical Activities, President of IEEE Computational Intelligence Society in 2004-05 and the ADCOM member in 2009-14 and earlier years. He chaired the IEEE TAB Periodicals Review and Advisory Committee and the IEEE TAB Periodicals Committee in 2010-11. In 2011 he was Vice-Chair of PSPB and member of PSPB Strategic Planning Committee in 2010-11.
Dr. Zurada has received a number of awards for distinction in research, teaching, and service including the 1993 Presidential Award for Research, Scholarship and Creative Activity, 1999 IEEE Circuits and Systems Society Golden Jubilee Medal, and the 2001 and 2014 Presidential Distinguished Service Awards for Service to the Profession. In 2013 he received the Joe Desch Innovation Award. He was a Distinguished Speaker of IEEE CIS in 2012-15. In 2003 he was conferred the Title of National Professor by the President of Poland. He also received four Honorary Professorships from Chinese universities. Since 2005 he has been a Member of the Polish Academy of Sciences, and was appointed as a Senior Fulbright Specialist for 2006-12.
Optimization & Decision Making in Intelligent Urban Transportation Systems
Abdelkader El Kamel
Ecole Centrale de Lille, France
Abstract: This plenary talk is concerned with the application of intelligent control theory in the future road transportation systems. With the development of human society, the demand for transportation is much stronger than any other period in history. More flexible and more comfortable, private cars are preferred by many people. Besides, the development of automobile industry reduces the cost to own a car, thus car ownership has been growing rapidly worldwide, especially in major cities. However, the increase of car number makes our society to suffer from traffic congestions, exhaust pollution and accidents. These negative effects force people to find ways out. In this context, the concept of “Intelligent Transportation Systems (ITS)” is proposed. Scientists and engineers have been working for decades to apply multidisciplinary technologies to transportation, in order to make it closer to our vision, such as safer, more efficient, more effort saving, and environmentally friendly.
One aspect is (semi-)autonomous systems. The main idea is to use autonomous applications to assist/replace human operation and decision. Advanced driver assistance systems (ADAS) are designed to assist drivers by alerting them when danger (e.g. lane keeping, forward collision warning), acquiring more information for decision-making (e.g. route plan, congestion avoidance) and liberating them from repetitive and trick maneuvers (e.g. adaptive cruise control, automatic parking). In semi-automatic systems, driving process still needs the involvement of human driver: the driver should set some parameters in the system, and he/she can decide to follow the advisory assistance or not. Recently, with the improvement of sensing technology and artificial intelligence, enterprises and institutes have been committed to the research and development of autonomous driving. In certain scenarios (e.g. highways and main roads), with the help of accurate sensors and highly precise map, hands-off and feet-off driving experience would be achieved. Elimination of human error will make the road transportation much safer, and better space utilization will improve the usage of road capacity. However, autonomous cars still need driver’s anticipation in certain scenarios with complicated traffic situation or limited information. The inner layout of autonomous cars would not be much different from current cars, because steering wheel and pedals are still necessary. The next step of autonomous driving is driver-less driving, in which the car is totally self-driven. The seat dedicated for driver would disappear and people on board would focus much. The car-sharing economy behind driverless cars would be enormous: in the future, people would prefer calling for a driver-less car when needed to owning a private car. Thus congestions and pollutions could be relieved.
Another way is cooperative systems. Obviously, the current road transportation notifications are designed for human drivers, such as traffic lights, turning lights and road side signs. The current autonomous vehicles are equipped with cameras dedicated to detect these signs. However, notifications designed for humans are not efficient enough for autonomous vehicles, because the usage of camera is limited by range and visibility, and algorithms should be implemented to recognize these signs. If the interaction between vehicles and environment is enabled, the notifications can be delivered via V2X communications, thus vehicles can be noticed in larger distance even beyond the sight, and the original information is more accurate than the information detected by sensors. When the penetration rate of driver-less cars is high enough, it would not be necessary to have physical traffic lights and signs. The virtual personal traffic sign can be communicated to individual vehicles by the traffic manager. In cooperative systems, an individual does not have to acquire the information all by its own sensors, but with the help of other individuals via communication. Therefore, autonomous intelligence can be extended into cooperative intelligence.
We will focus on the development of applications to improve the safety and efficiency for intelligent transportation systems in context of autonomous vehicles and V2X communications in the scope of cooperative systems. Control strategies are designed to define the way in which the vehicles interact with each other and with infrastructures. The main aspects which will be discussed are summarized by:
- A PSO (particle swarm optimization)-based platoon control algorithms for following vehicles in platoons. Constraints like control input, engine power and maximum speed are considered when designing the cost function. It is an attempt of applying bionic optimization algorithm in vehicular platoon control. The parameters are regulated to response to potential real-time usage in the future.
- Cooperative Adaptive Cruise Control in Vicinity of Intersections (CACC-VI) to improve the intersection’s throughput by taking advantage of the “opportunity space” on road. The vehicular platoons are reorganized to accelerating platoon and decelerating platoon based on vehicles’ dynamic abilities.
- For intersections without crosswalk, there are no other individuals but vehicles. In this case, except traffic lights, there can have some other management methods with the help of V2X communications. Decentralized Autonomous Intersection Control (DAIC) is designed for light traffic situations, to control vehicles to get through the intersection with no collision and less delay. Before arriving at the intersection, a vehicle demands the space-time occupancy situation from the intersection manager, and based on the motion of the preceding vehicle, it will adjust its own velocity to a collision-free value and it should maintain this velocity until fully getting through the intersection. Basically, DAIC is an enumerative negotiation-based method. A simulation testbed to test the intersection control algorithm is designed in UML then realized by the combination of
- Matlab and a traffic simulator SUMO.
- Trajectory Planning based Autonomous Intersection Management (TP-AIM) for all traffic densities is presented. Based on the occupancy information from the manager, the vehicle searches for safe entering windows. And according to these windows and the future motion of the preceding vehicle, a dynamic programming based method is used to plan the vehicle’s trajectory. The related communication procedure is also described. Compared to traditional and adaptive traffic lights, the efficiency of TP-AIM is greatly improved. The principle of TP-AIM could be used in different types of intersections even in heavy traffic conditions.
Biography: Professor El Kamel received the Engineering Diploma & Master of Science from Ecole Centrale in 1990; the Ph.D. in Feb. 1994 and the HCR “Habilitation to Conduct Research” (required to become Full Professor in France) in Nov. 2000, all in Computer & Systems Engineering. Full Professor at Centrale Lille, Dr. El Kamel is also appointed as Permanent Regular Visiting Professor in China with 2-to-3 months visits a year since 2008 (BUAA, BIT, Ecole Centrale Peking & University of Macao), Tunisia with 3-to-4 visits a year since 1995 (HEC Carthage, ENIT, EPT, SUP’COM, ISG…), Chili (USACH, U. Valparaiso, U. of Magellan), Romania (PUB), Canada (U. of Laval), India (IIT Kharagpur) and Sweden (KTH).
He was, among others, the Program Chair of the IEEE Conference CESA’2012 held in Santiago, Chili in April 2012; the Conference Chair of “Intelligent Automation and Control Track” in the 17thWorld Automation Congress held in Budapest in July 2006; the Organizer and General Chair of the IEEESMC’02 Conference held in Tunisia in October 2002; the Organizer and General Chair of the IEEESMC/IMACS Multi-conference CESA’98 held in Hammamet in April 1998. He received several international awards, among others an IEEE-CESA Outstanding Contributions Award in April 2012; a WAC Distinguished Contribution Award in July 2006 “for his dedicated and outstanding contributions to the success of WAC’06”; an IEEE Outstanding Contribution Award in October 2002 “for leadership in organization the SMC’02 conference”; an IEEE Outstanding Contribution Award in October 1998 “for leadership in organization of the SMC sponsored CESA’98 conference and for many contributions to research and scholarship”.
Dr. El Kamel is Chair of the Technical Committee on “Control of Uncertain Systems” for IEEE-SMC and President of the French IEEE-SMC Chapter since 2002; Member elect of the Board of Governors of the IEEE France Section (2005-2012); Co-Chair then Chair of the IEEE-SMC “Student Activities Committee” (1998-2004). Member of the IFAC TC3.2 “Computational Intelligence in Control” since 2005; he was also Member elect of the National Council of Universities (CNU), which evaluates & promotes professors in France (2000-2004). He has been invited speaker for more than 50 plenary lectures or tutorials in International Conferences and is on the Program Committee of more than 150 IEEE SMC & CSS, IFAC and several other conferences.
His major research interests include intelligent systems control & optimization. Applying Intelligent Technologies, Virtual Reality & Optimization Techniques in Intelligent Transportation Systems and Mobile Cooperative Robots are among the current focus of his works. He has published more than 150 technical papers in International Journals and Conferences; has participated to 5 books and has edited more than 15 proceedings or CD-ROM proceedings of conferences and workshops. He has supervised 17 PhDs, several in the frame of the Chinese CSC-sponsored scholarships, industrial partnerships, international co-supervisions… All of his PHD students are hired and occupy high academic or private company positions now.
Since November 2016, Prof. El Kamel is Cabinet Staff Member of the Tunisian Minister of Higher Education & Research. He is in charge with International Cooperation mainly with EU (2020 project), China & Latin America.
Human-robot collaboration for smart factories
Centre for Research and Advanced Studies (CINVESTAV, Mexico). Robotics and Advanced Manufacturing Department
Abstract: Industrial robots are reliable machines for manufacturing tasks such as assembly, welding, painting and palletizing operations. They have been traditionally programmed by an operator using a teach pendant in a point-to- point scheme with limited sensing capabilities such as industrial vision systems and force/torque sensing. Today, industrial robots can react to environment changes specific to their task domain but are still unable to learn skills to effectively use their current knowledge. The need for such a skill in unstructured environments where knowledge can be acquired and enhanced is desirable so that robots can effectively interact in multimodal real-world scenarios.
In this paper, an alternative approach based on Artificial Neural Networks to embed and effectively enhance knowledge into industrial robots working in manufacturing scenarios is reviewed. During learning, the robot uses its sensorial capabilities resembling a human operator to successfully accomplish the requested operation in assembly and welding. Current work, issues and experiments are presented and future work envisaged regarding learning in distributed systems in smart factories involving human-robot interaction.
Biography: Dr. Lopez-Juarez graduated with a BEng in Mechanical and Electrical Engineering from The National Autonomous University of Mexico (UNAM) in 1991. He obtained an MSc degree in Instrument Design and Application from The University of Manchester Institute of Science and Technology (UMIST), U.K. in 1996 and a PhD in Intelligent Robotics from The Nottingham Trent University, U.K. in 2000. His areas of interest are in Instrumentation, Self-adaptive Industrial Robots, Neural Networks and Machine Vision. Dr Lopez-Juarez has published over 160 papers, 10 book chapters, has supervised 7 PhD thesis to completion, 12 MSc thesis and 7 BEng students. He has 2 patents and has been responsible for several technological projects and technology transfer within the industry. He is member of the National Researchers Systems in Mexico (SNI), level II. He was the founder and leader of the Mechatronics and Intelligent Manufacturing Systems Research Group at CIATEQ, Advanced Technology Centre A.C. during 2000-2006. Founder of the Robotized Welding Laboratory at COMIMSA during a Postdoctoral stay in the period 2008-2010. He was appointed as Visiting Researcher at the National Centre for Food Engineering (NCEFE) at Sheffield Hallam University in the UK during 2015-2016. Currently, he is the leader of the Intelligent Manufacturing Laboratory and Academic Coordinator (from Aug, 2016) for the Robotics and Advanced Manufacturing Systems Research Group at CINVESTAV in Mexico.
Data Management Support for moving-object data
M. Andrea Rodríguez
Department of Informatics Engineering and Computer Science at the University of Concepcion, Chile.
Abstract: Due to the current advances in sensor networks, wireless technologies, and RFID-enabled ubiquitous computing, data about moving-objects (also referred as trajectories) is an example of massive data relevant in many real applications. Think in the notion of Smart Cities, which implies the use of information and communication technologies in combination with social and human capital to enhance the quality of life of a community. In this context, the optimization of the transportation systems by control surveillance, road planning, and road navigation systems are of special relevance. Trajectories can be reconstructed from, for example, modern cellular phones with GPS devices or from smartcards (that users can recharge with money) of public transportation systems. In this presentation, I cover past and current research efforts addressing the modeling and processing of moving object data. I review data models to represent where and when objects have been or will be. I consider for query processing the main types of queries and data structures and state the challenging issues of our current research.
Biography: M. Andrea Rodríguez received her Ph.D. in Spatial Information Science and Engineering from the University of Maine-USA in 2000 thanks to a Fulbright fellowship and a research-assistant grant under the supervision of Dr. Max Egenhofer. She returned to Chile in 2000, joined the Department of Informatics Engineering and Computer Science at the University of Concepcion, became a full professor in 2008, and is currently head of the Department. Her areas of interest include spatial and spatio-temporal databases and information retrieval. She has been a principal investigator of six Fondecyt grants since 2001, has directed an ECOS / CONICYT project (Chile-France cooperation), was a researcher at the Millennium Nucleus Research Center of the Web, and is currently part of the Institute of Engineering Complex Systems and the Basal Fund for Biotechnology and Bioengineering, and the BIRDS (Bioinformatics and Information Retrieval) project funded by the European Union. Products of her research are 17 publications in ISI indexed journals such as Information Systems, IEEE Transactions on Knowledge and Data Engineering, IEEE transactions on Evolutionary Computation, International Journal of Geographic Information Science, Knowledge and Information Systems, and more than 35 publications in international conferences such as SSTD, SPIRE, DCC, and ADBIS. She was PC co-chair of the first two international conferences of GeoSpatial Semantics 2005 and 2007, and has been a member of several program committees (COSIT, GIScience, ISWC, SeCoGis, among others).
ReRAM: An Emerging Device Technology for Storage, Computing and Learning
Department of Electronic Engineering, Universidad Técnica Federico Santa María, Valparaíso, Chile. Previously with the Centro de Investigación en Nanotecnología y Materiales Avanzados (CIEN-UC), Department of Electrical Engineering, Pontificia Universidad Católica de Chile (PUC), Santiago, Chile
Abstract: Resistive switching electronic devices (ReRAM devices or memristors) have been known ever since the 60s. However, owing to the physical realization of the Chua’s memristor by the Hewlett-Packard Laboratories in 2008, new research tracks and trends in modern circuit design have indeed been created. The memristor, a nanoscale, nonvolatile, two-terminal resistive device whose resistance changes depending on the input signal applied to its terminals, is currently being explored for several emerging applications regarding upgraded and novel, energy-efficient digital/analog implementations such as nonlinear (chaotic) circuits, storage systems, logic circuits, neuromorphic and generally unconventional circuit architectures. This talk covers a timely topic of academic and industrial interest, aiming to stimulate further research on memristive devices, circuits, and systems. It particularly considers the design and development of nanoelectronic circuits, systems and computing architectures focusing on memristor as the main storage and computing element. The ultimate goal is to explore and report the major related challenges and present state-of-the-art research directions for the smooth transition from conventional circuit technologies to emerging, beyond von Neumann computing nanotechnologies. The presented material spans from fundamental device modeling to emerging, dense, multi-level storage system architectures and novel, unconventional circuit design methodologies, targeting advanced analog/digital, massively parallel, neural-based computational and learning structures.
Biography: Dr. Ioannis Vourkas was born in Kozani, Greece, in 1985. He received the M.Eng. (Diploma) and Ph.D. degrees, both in Electrical and Computer Engineering (ECE), from the Democritus University of Thrace (DUTh), Xanthi, Greece, in 2008 and 2014, respectively. Currently he is faculty member of the Department of Electronic Engineering, Universidad Técnica Federico Santa María, Valparaíso, Chile. Previously he was Postdoctoral Researcher with the Centro de Investigación en Nanotecnología y Materiales Avanzados (CIEN-UC), Department of Electrical Engineering, Pontificia Universidad Católica de Chile (PUC), Santiago, Chile. His research emphasis is on novel nanoelectronic circuits and architectures comprising memristors. Specifically, his research so far focused on the modeling and simulation of memristors, the design and simulation of analog/digital circuits, nonvolatile (multi-level) memory architectures with memristors, resistive networks and neural networks based on memristors, as well as electronic systems implementing computational models and algorithms of artificial intelligence using memristors (e.g. for maze-solving, shortest path and traveling salesman problem, etc.). In all the aforementioned research topics, he is the main author of one of the first memristor-related monographs of the literature entitled “Memristor-Based Nanoelectronic Computing Circuits and Architectures” including a foreword by Prof. Leon Chua, published by Springer in 2015, of one book chapter in “Memristor Networks” (A. Adamatzky, L. Chua, eds.), of more than 17 journal articles and of several technical papers presented in international conferences. Currently, his research endeavor is funded through a three-year CONICYT FONDECYT Postdoctorado Chilean government research grant (2015-2018) and involves the development of novel bio-inspired and bio-mimicking memristive circuit models, memristive artificial neural processing and learning systems, and massively parallel unconventional memristive computing approaches targeting state-of-the-art nanoelectronic hardware platforms. His research interests further include modern unconventional computing, software and hardware aspects of parallel complex computational (bio-inspired) circuits and systems, cellular automata theory and applications, circuit design and simulation.
HVDC Grids and Renewable Energy Integration
Department of Systems Engineering and Control, Technical University of Valencia, Spain
Abstract: Renewable Energy is a key contributor to fight climate change. Latest bids in Europe and elsewhere have shown that renewable energy can be provided at competitive market price. Even some of the new off-shore wind power plants to be installed in the North Sea will operate without any subsidies, competing directly in electricity markets with other sources of energy.
Nevertheless, there is a continuous drive to make bulk wind energy and other renewable energy sources more and more competitive. Substantial research is taking place to reduce the total cost of electricity generated by off-shore wind farms.
A key component is the reduction of grid connection and transmission costs. High Voltage DC connections are used for the connection of large off-shore wind farms and large electric systems. This kind of links are paramount to bring large amounts of electricity across large distances. Therefore, both cost reduction and increase on reliability are constant drivers for more advanced HVDC technology.
This talk will address the following topics:
- Technical hurdles for high penetration of renewable energy.
- State of off-shore wind farms in Europe.
- State-of-the-art HVDC connection technologies.
- Power Electronics and their control for the connection of off-shore wind farms using HVDC links, including diode rectifiers.
- European research on meshed HVDC grids.
Biography: Prof. Ramon Blasco-Gimenez obtained his BEng. degree from the Technical University of Valencia, Spain, in 1992, and his Ph.D. degree in Electrical and Electronic Engineering from the University of Nottingham, U.K., in 1996.
From 1992 to 1995, he was a Research Assistant in the Department of Electrical and Electronic Engineering, University of Nottingham. He is currently a Professor at the Dept. of Systems Engineering and Control of the Technical University of Valencia, where he teaches advanced control techniques and control of drives.
He has been a consultant on integration of wind farms in weak grids and to large wind farm operators on risk based operation and maintenance of off-shore wind farms. His research interests include control of motor drives, wind power generation, off-shore wind farms and grid integration of renewable energy, including pioneering work on the use of diode rectifiers for the HVDC connection of off-shore power plants. Prof. Blasco-Gimenez has worked in 38 research projects in the aforementioned areas, leading 15 of them, with more than 125 papers published and 3 patents filed.
Prof. Blasco-Gimenez has been a co-recipient of the 2005 IEEE Transactions on Industrial Electronics Best Paper Award. He is a Senior Member of the IEEE, member of the Electrimacs Committee, Chartered Engineer (U.K.), member of the Institute of Engineering and Technology, guest researcher of the Solar Energy Research Centre SERC-Chile and chair of the IEEE Industrial Electronics Society Renewable Energy Technical Committee (2014-2016). He has been guest scholar at the National Cheng Kung University of Taiwan and National Taiwan University of Science and Technology.
He has been the chair of the 11th Electrimacs 2014 conference and invited speaker in several IEEE sponsored conferences. He has been guest editor of the IEEE Transactions on Energy Conversion special issue on Microgrids and is currently associate editor of the Elseiver-IMACS Journal on Mathematics and Computers in Simulation and a member of the IEEE Industrial Electronics Society Publications Committee.
Control challenges in dealing with Cyber-Physical Systems
Instituto Universitario de Automática e Informática Industrial, Universitat Politècnica de València, Spain
Abstract: A cyber-physical system integrates computing, communication and storage capabilities within entities in the physical world. Traditionally, control designers and real-time computer and telecommunication experts work separately. The first conceive the control algorithms based on the required performance and the process knowledge, regardless their subsequent implementation, whereas the computer experts deal with the control code without paying much attention to the impact of the code execution in the control performance, and the communication experts provide the link, assuming data accessibility and validity. But they are interlaced and the full design should be jointly treated, mainly if the control tasks share resources with some other activities and these resources are limited. In this talk, the real-time control design and implementation will be reviewed, mainly from the control perspective.
Global requirements in control applications in time critical environments, such as automobile, aerospace or flight control, where multiple interactive control loops are implemented, are reviewed. Special attention is devoted to new and widespread control scenarios where the controller is not anymore implemented in a full dedicated computer without resources constraints, but sharing and competing for computing, storage and communication facilities with several other tasks. Embedded control systems, networked control systems and event-based control systems challenge the design of the control and its implementation where architectural issues play a relevant role in the controlled system performance. Some key concepts interacting with both, the control performance and the control implementation, such as the control effort or the control kernel are emphasized and some general directions in the co-design are summarized.
Biography: Pedro Albertos, past president of IFAC (the International Federation of Automatic Control) in 1999-2002, IFAC Fellow, IFAC Advisor and Life Senior Member of IEEE, is a world recognized expert in real-time control, leading several projects in the field. Full Professor since 1975, he is currently Emeritus Professor at Systems Engineering and Control Dept. UPV, Spain. He is Doctor Honoris-Causa from Oulu University (Finland) and Bucharest Polytechnic (Rumania). Invited Professor in more than 20 Universities, he delivered seminars in more than 30 universities and research centers. Authored over 300 papers, book chapters and congress communications, co-editor of 7 books and co-author of “Multivariable Control Systems” (Springer 2004) and “Feedback and Control for Everyone” (Springer 2010). This last book has received the Harold Chesnut best text-book award at the past IFAC World Congress in Toulouse (Juy 2017). He is also associated editor of Control Engineering Practice and Editor in Chief of the Spanish journal RIAI. His research interest includes multivariable control and non-conventional sampling control systems, with focus on time delays and multirate sampling patterns.
Feedback e ingeniería: una clave fundamental para la innovación
Jaime Alvarez Gerding
Secretaría Ejecutiva y Gerente de Estudios. Consejo Nacional de Innovación para la Competitividad (CNIC)
Abstract: Algunas de las más grandes innovaciones en la historia de la humanidad fueron hechas posibles gracias a la aplicación de esquemas de feedback. En esta charla examinaremos algunas de dichas innovaciones desde el punto de vista de la ingeniería de control automático para iluminar nuestra comprensión más allá de lo exclusivamente técnico. Revisaremos el contexto en que estas innovaciones aparecen y cómo reconfiguran el mundo de lo posible para hacernos cargo de preocupaciones de la humanidad. Luego haremos una breve provocación intelectual sobre las múltiples dimensiones de la incertidumbre en el mundo actual y plantearemos cómo la capacidad de instalar “working feedback loops” puede hacer una gran diferencia. Desde la medicina hasta los restaurantes, pasado por la ingeniería electrónica y mecánica, esta charla es a la vez una provocación y un llamado de atención a los ingenieros para que nos hagamos responsables de ser actores relevantes en la construcción de nuestro mundo.
Biography: Ingeniero Civil Electrónico (UTFSM) y MBA (UAI) con extensa experiencia en diversos sectores económicos (energía, retail, tecnología y consultoría). En los últimos años se ha desempeñado en el sector público, con un foco especial en la coordinación y conducción de conversaciones estratégicas asociadas a desafíos nacionales de futuro en temas como minería, desastres naturales y recursos hídricos. Su interés principal está en las formas de abordar la incertidumbre, tanto en el sector público como en el sector privado. Bilingüe (Español – Inglés).
Optimización de redes inalámbricas complejas: es machine learning la panacea?
WINE research group of the Universitat Oberta de Catalunya (UOC)
Abstract: Los esfuerzos dedicados a la optimización de redes inalámbricas se han basado tradicionalmente en la caracterización del comportamiento y de las interacciones de los dispositivos de red. Por este motivo el nivel de complejidad que estos métodos pueden gestionar es limitado y habitualmente es necesario realizar simplificaciones que distan del comportamiento real. Pero ante la creciente complejidad de las redes actuales, sobretodo en entornos urbanos, debida a los incrementos en densidad, heterogeneidad y demanda de tráfico, se hace necesario el uso de métodos alternativos. Una de las alternativas que más atención está captando en la comunidad científica es el uso de machine learning ya que los algoritmos que usan estas técnicas son capaces, en teoría, de optimizar el rendimiento basándose únicamente en el resultado de las acciones tomadas. En esta charla, a través de un ejemplo concreto como es el de coexistencia de redes WiFi con redes celulares en las bandas libres, veremos qué oportunidades presentan estos algoritmos pero también daremos una mirada crítica a los retos que se deben superar para garantizar su correcto funcionamiento en la práctica.
Biography: Cristina Cano obtuvo su doctorado en Tecnologías de la Información, Comunicación y Medios Audiovisuales de la Universitat Pompeu Fabra (UPF) en 2011. Desde entonces ha trabajado como investigadora en el Hamilton Institute de la National University of Ireland, Maynooth (2012-2014), en Trinity College Dublin (2015) y en Inria- Lille en Francia (2016). Actualmente es investigadora senior en el grupo de investigación WINE de la Universitat Oberta de Catalunya (UOC). Cristina cuenta con 13 artículos publicados en revistas científicas y más de 30 artículos publicados en conferencias internacionales. La organización N2Women la incluyó en la lista “10 Women in Networking/Communications That You Should Watch” en Agosto de 2016. Sus intereses incluyen la coexistencia de redes heterogéneas así como la asignación de recursos distribuida y la optimización de red.