MED'13

21st Mediterranean Conference on Control and Automation

June 25-28, 2013

Minoa Palace Resort & Spa

Platanias-Chania, Crete - GREECE

MED'13 Program

Program Details

Program Summary

Keynote Lectures

K1: ROBUST ADAPTIVE CONTROL: INTERPRETATIONS, EXPECTATIONS AND REALITY

Petros A. Ioannou
University of Southern California

Abstract: Adaptive Control has a long history full of exciting results, new algorithms, successful applications but also some disappointments. These disappointments arise due to high expectations in looking for a miracle scheme that treats an unknown plant as a black box and yet meets all robustness and performance requirements. This talk presents a short survey of these developments and separates the drawbacks of some adaptive schemes that are originated from the design assumptions and those that are inherent in any design because of the quality of information in the input/output data. We revisit the MIT rule and sensitivity approaches as well as recent adaptive approaches whose performance and stability properties are limited by design and show how these drawbacks can be removed. We show that adaptive control despite its failure to meet unrealistic expectations it performs, as one would expect it to perform by processing available input/output data. One sophistication of adaptive control is to induce self- excitation when there is limited information about the unknown plant in the input/output data and the estimated parameters drift to values that are destabilizing. We present some successful applications in adaptive disturbance rejection of periodic disturbances for laser beam control and other applications.

Short Bio: Petros A. Ioannou received the B.Sc. degree with First Class Honors from University College, London, England, in 1978 and the M.S. and PhD degrees from the University of Illinois, Urbana, Illinois, in 1980 and 1982, respectively. In 1982, he joined the Department of Electrical Engineering-Systems, University of Southern California, Los Angeles, California. He is currently a Professor in the same Department and holds courtesy appointments with the Department of Aerospace and Mechanical Engineering and the Department of Industrial and Systems Engineering. His research interests are in the areas of adaptive control, neural networks, vehicle dynamics and control, aerospace control and intelligent transportation systems. Dr. Ioannou is the recipient of a 1985 Presidential Young Investigator Award for his research in Adaptive Control. In 2009 he received the IEEE ITSS Outstanding Application Award for his work on Adaptive Cruise Control Systems and the 2009 IET Achievement Medal in control systems by the Institute of Engineering and Technology (IET). In 2012 he received the IEEE ITSS Outstanding Research Award. He has been an Associate Editor for the IEEE Transactions on Automatic Control, the International Journal of Control, Automatica and IEEE Transactions on Intelligent Transportation Systems. He served as Associate Editor at Large of the IEEE Transactions on Automatic Control and Chairman of the IFAC Technical Committee on Control of Transportation Systems. He is a member of the Board of Governors of the IEEE Intelligent Transportation Society. Dr. Ioannou is a Fellow of IEEE, IFAC and IET and the author/co-author of 8 books and over 250 research papers in the area of adaptive systems, nonlinear control, neural networks, nonlinear dynamical systems and intelligent transportation systems.

K2: COOPERATIVE CONTROL: OPTIMALITY, DIFFERENTIAL GAMES, AND REINFORCEMENT LEARNING ON GRAPHS

F. L. Lewis
Fellow IEEE, Fellow IFAC,
Moncrief-O'Donnell Endowed Chair
University Distinguished Scholar Professor
University Distinguished Teaching Professor
The University of Texas at Arlington, Texas, USA

Abstract: Distributed systems of agents linked by communication networks only have access to information from their neighboring agents, yet must achieve global agreement on team activities to be performed cooperatively. Examples include networked manufacturing systems, wireless sensor networks, networked feedback control systems, formations, and the internet. Sociobiological groups such as flocks, swarms, and herds have built-in mechanisms for cooperative control wherein each individual is influenced only by its nearest neighbors, yet the group achieves optimal synchronization behaviors. It was shown by Charles Darwin that local interactions between population groups over long time scales lead to global results such as the evolution of species. Natural decision systems incorporate notions of optimality, since the resources available to organisms and species are limited. Optimal feedback control design has been responsible for much of the successful performance of engineered systems in aerospace, industrial processes, vehicles, ships, robotics, and elsewhere since the 1960s. Optimal control design is performed offline by solving optimal design equations including the algebraic Riccati equation and the Game ARE. Optimal design generally requires that the full system dynamics be known, and is limited by the properties of communication topologies.
Optimality on Graphs: Global optimal control of distributed systems on communication graphs is complicated by the fact that, for general LQR performance indices, the resulting optimal control is not distributed in form. Therefore, it cannot generally be implemented on a prescribed communication graph topology by using only local neighbor information. A condition is given for the existence of any optimal LQR controllers that can be implemented on a given graph in distributed fashion. This condition shows that for the existence of global optimal controllers of distributed form, the performance index weighting matrices must be selected to depend on the graph structure.
Graphical Games: A novel form of multi-player game among agents in a communication graph is formulated where each agent is allowed to interact only with its neighbors. A new notion of Nash equilibrium is defined that is suitable for graphical games and guarantees that that all agents achieve synchronization while optimizing their own value functions.
Reinforcement Learning on Graphs: This talk will discuss some new cooperative control structures for learning online the solutions to multi-player differential games on graphs. Techniques from reinforcement learning are used to design a new family of adaptive controllers based on actor-critic mechanisms that converge in real time to optimal control and game theoretic solutions on graphs.

Short Bio: Frank Lewis was born in Wurzburg, Germany, subsequently studying in Chile and Gordonstoun School in Scotland. He obtained the BS in Physics/Electrical Engineering and the Master's of Electrical Engineering Degree at Rice University in 1971. He spent six years in the U.S. Navy, serving as Navigator aboard the frigate USS Trippe (FF-1075), and Executive Officer and Acting Commanding Officer aboard USS Salinan (ATF-161). In 1977 he received the MS in Aeronautical Engineering from the University of West Florida. In 1981 he obtained the Ph.D. degree at The Georgia Institute of Technology in Atlanta, where he was employed as a professor from 1981 to 1990. Registered Professional Engineer in the State of Texas and Chartered Engineer, U.K. Engineering Council. Charter Member (2004) of the UTA Academy of Distinguished Scholars. Member UTA Academy of distinguished Teachers. Founding Member of the Board of Governors of the Mediterranean Control Association. Author of 6 U.S. patents and books including Optimal Control, Optimal Estimation, Applied Optimal Control and Estimation, Aircraft Control and Simulation, Control of Robot Manipulators, and Neural Network Control.

K3: COOPERATING UAS: FROM INFORMATION ACQUISITION TO PHYSICAL INTERACTIONS

Anibal Ollero
Universidad de Sevilla, Spain

Abstract: In this plenary talk we will discuss some control and automation issues related to cooperating multiple Unmanned Aircraft Systems (UAS). We will first consider the exploitation of capabilities of heterogeneous Unmanned Aerial Vehicles (UAVs) in detection and monitoring missions. Then, we will discuss and analyze the integration of UAS with ground wireless sensor and actuator networks. Next, we will present results of the EC-SAFEMOBIL (FP7- ICT - 288082) project dealing with new estimation/prediction and cooperative control methodologies and their practical application to autonomous landing in mobile platforms, surveillance and tracking with multiple UAVs. The MUAC-IREN FP7 project dealing with cooperative long endurance missions with multiple UAVs will also be introduced. The second part of the talk will be devoted to physical interactions among UAVs and interactions between UAVs and objects in the environment. The joint load transportation problem using multiple aerial vehicles will be presented, followed by results of the ARCAS project (FP7-ICT- 287617) dealing with the cooperation of multiple aerial robots with manipulators, including quadrotors and helicopters with arms and hands for grasping and assembly.

Short Bio: Aníbal Ollero (http://grvc.us.es/aollero) is Full Professor and Head of the GRVC Group (60 researchers) at the University of Seville, and Scientific Advisor of the Center for Advanced Aerospace Technologies in Seville. He has been full professor at the Universities of Santiago de Compostela and Malaga in Spain, and researcher at Carnegie Mellon University (Pittsburgh, USA) and LAAS-CNRS (Toulouse, France). He is author/co-author of 484 publications, including 9 books and 113 papers in SCI journals. He led about 130 projects and he is currently the coordinator of the ARCAS and EC-SAFEMOBIL FP7 Integrated Projects of the European Commission, and associated coordinator of FP7 PLANET and CONET Network of Excellence. He is the recipient of 13 national and international awards for his R&D activities including the second 2010 EUROP-EURON Technology Transfer award and the IV Javier Benjumea award by Scientific Excellence and Social Impact. He has been the advisor of 26 PhD students. He is currently the President of the Spanish Robotics Society SEIDROB.

K4: A DISTRIBUTED NETWORKED APPROACH TO FAULT DIAGNOSIS OF LARGE-SCALE SYSTEMS

Thomas Parisini
Imperial College London (UK) and University of Trieste (I)

Abstract: This lecture deals with a class of systems that are becoming ubiquitous in the current and future "distributed world" made by countless "nodes", which can be cities, computers, people, etc., and interconnected by a dense web of transportation, communication, or social ties. The term "network", describing such a collection of nodes and links, nowadays has become commonplace thanks to our extensive reliance on "connections of interdependent systems" in our everyday life, for building complex technical systems, infrastructures and so on. In an increasingly "smarter" planet, it is expected that such interconnected systems will be safe, reliable, available 24/7, and of low-cost maintenance. Therefore, health monitoring and fault diagnosis are of customary importance to ensure high levels of safety, performance, reliability, dependability, and availability. For example, in the case of industrial plants, faults and malfunctions can result in off-specification production, increased operating costs, production line shutdown, danger conditions for humans, detrimental environmental impact, and so on. Faults and malfunctions need to be detected promptly and their source and severity should be diagnosed so that corrective actions can be taken as soon as possible. In the talk, an adaptive approximation- based distributed and networked fault diagnosis approach for large-scale nonlinear systems will be dealt with, by exploiting a "divide et imperia" approach in which the overall diagnosis problem is decomposed into smaller sub-problems, which can be solved within “local” computation and communication architectures. The distributed detection, isolation and identification task is broken down and assigned to a network of "Local Diagnostic Units", each having a "local view" of the system. These local diagnostic units are allowed to communicate with each other through an information network to cooperate on the diagnosis of system components that may be shared or interconnected.

Short Bio: Thomas Parisini received the PhD degree in Electronic Engineering and Computer Science in 1993 from the University of Genoa. He was with Politecnico di Milano and since 2010 he holds the Chair of Industrial Control at Imperial College London. Since 2001 he is also Danieli Endowed Chair of Automation Engineering with University of Trieste and in 2009-2012 he was Deputy Rector of the University of Trieste. He authored or co-authored more than 250 research papers in archival journals, book chapters, and international conference proceedings. His research interests include neural-network approximations for optimal control problems, fault diagnosis for nonlinear and distributed systems and nonlinear model predictive control systems. He is a co-recipient of the 2004 Outstanding Paper Award of the IEEE Trans. on Neural Networks and a recipient of the 2007 IEEE Distinguished Member Award. He is involved as Project Leader in several projects funded by the European Union, by the Italian Ministry for Research, and he is currently leading consultancy projects with some major process control companies (ABB, Danieli, Duferco, Electrolux, among others). Thomas Parisini is the Editor-in- Chief of the IEEE Trans. on Control Systems Technology. He was the Chair of the IEEE Control Systems Society Conference Editorial Board and a Distinguished Lecturer of the IEEE Control Systems Society. He was an elected member of the Board of Governors of the IEEE Control Systems Society and of the European Control Association (EUCA) and a member of the board of evaluators of the 7th Framework ICT Research Program of the European Union. Prof. Parisini is currently serving also as an Associate Editor of the Int. J. of Control and served as Associate Editor of the IEEE Trans. on Automatic Control, of the IEEE Trans. on Neural Networks, of Automatica, and of the Int. J. of Robust and Nonlinear Control. Among other activities, he was the Program Chair of the 2008 IEEE Conference on Decision and Control and he is General Co- Chair of the 2013 IEEE Conference on Decision and Control. Thomas Parisini is a Fellow of the IEEE.

K5: ADVANCED SENSING ARRAYS FOR STRUCTURAL MONITORING AND CONTROL OF AEROSPACE VEHICLES

W. Lance Richards
(With contributions from: Allen R. Parker, Jr, Anthony Piazza, and Patrick Chan)
Aerospace Research Technical Manager
NASA Dryden Flight Research Center
Edwards, California

Abstract: This plenary lecture provides an overview of the research and technology development performed at NASA Dryden Flight Research Center in support of advanced fiber optic sensors for structural monitoring and control applications. Merits and theory of fiber optic sensor technology are presented to provide a fundamental understanding of the technical benefits that can be realized by the aerospace community by including advanced sensing technology within onboard monitoring and control systems. Ground- and flight-based systems that have been developed and flight validated for vehicle applications are presented. Recent examples of large-scale vehicle application of these advanced sensory networks are presented with a view toward automated monitoring and control of aerospace vehicles.

Short Bio: Dr. W. Lance Richards joined NASA's Dryden Flight Research Center in 1985 and has served as technical leader of various research groups in the Research Engineering Directorate since 1995. He currently serves as Aerospace Research Technical Manager and leads NASA Dryden's research and development efforts for fiber optic sensing, structural health monitoring, and nondestructive evaluation technology. Dr. Richards has conducted research in fiber-optic smart structures and served as Principal Investigator of structural health monitoring flight experiments at NASA Dryden since 1999. He has authored more than 80 technical reports and serves as Session Organizer and Chair for several conferences and symposia. His talk will highlight some of the recent advancements that NASA Dryden has made in fiber optic sensing technology for flight applications of aerospace structures.

Tutorials / Workshops

T1: Enabling Secure, Scalable Microgrids with High Penetration Renewables

Dr. Steven Glover
Sandia National Laboratories
Albuquerque, NM

Dr. Rush D. Robinett III
Michigan Technological University
Houghton, MI

Details: Please download the detailed tutorial agenda.

Summary: This workshop covers technologies for realizing high-performance, agile microgrids. Attendees will be introduced to key challenges in modeling, control, optimization and R&D testing for microgrids capable of operating with high levels of agility and renewable penetration. It is structured as six, self-contained modules. Each module summarizes the current literature, describes challenges and presents current methods for achieving solutions. Opportunities for discussion are available to foster new collaborations and ideation. A workshop specific reference list has been included from which a large portion of the workshop material will draw upon.

The basis of the workshop summarizes a Sandia National Laboratories sponsored three year Grand Challenge Laboratory Directed Research and Development (GC/LDRD) effort. The vision is to develop tools that enable design and trade-off analyses of networked microgrids spanning the space from conventional to 100% stochastic generation.

Energy surety is a matter of national and international security. The present electric grid is based on a foundation created over 100 years ago. The infrastructure is topologically fixed, power sources are centralized and dispatchable (completely controllable), the loads are largely predictable, and the control of power flow at the load is essentially open-loop making it vulnerable to terrorist attacks, natural disasters, infrastructure failures, and other disruptive events. Further, this grid model limits renewables and other distributed energy sources from being economically and reliably integrated into the grid because it has been optimized over decades for large, centralized power generation sources.

Although issues of cost-effective and reliability have long been regarded as fundamental considerations of our present energy infrastructure, in recent years both the Department of Energy (DOE) and the Department of Defense (DoD) have turned attention towards energy surety -- providing cost effective supplies of energy that are reliable, safe, secure, and sustainable. However, forward-looking energy surety requires the development of novel intelligent grid architecture in order to be robust, effective, and efficient.

Researchers will leverage capabilities and theories unique to Sandia, creating advanced models, nonlinear control theory, system control theory, and informatics and flexible experimental hardware testbeds as tools to enable the analysis and design of these complex systems. Ultimately, the goal is to advance and integrate new theories on distributed nonlinear control, agent-based closed-loop controls, informatics, and experimental microgrid hardware testbeds to enable adaptive microgrids and networked microgrids with guaranteed stability and transient performance.

By advancing these sciences and technologies, we are enabling reliable, resilient, secure, and cost effective microgrids and interconnected microgrids making up the Smart Grid of the future. One of our primary goals of the GC/LDRD is to disseminate technical aspects of the project to the technical community for which the MED'13 workshop provides an ideal setting.

T2: Who's Afraid of Fractional Order Laplace?

Dr. Cristina I. Muresan
Technical University of Cluj-Napoca
Romania

Dr. Clara M. Ionescu
Ghent University
Belgium

Details: Please download the detailed tutorial agenda.

Summary: Fractional calculus is a powerful emerging mathematical tool in engineering, which consists of a generalization of the classical integer-order derivatives and integrals to non−integer orders. From time domain to Laplace domain, such a generalization implies computing a Laplace operator to a non-integer order, which makes it interesting for application in control engineering.

Although it originated from abstract science as mathematics, further applied in chemistry, physics and biology, the concept of "non-integer Laplace operator" has gained a lot of interest from the research community in the last two decades. With the aid of powerful computers, the complex mathematical computations are no longer a bottleneck and these emerging powerful tools are now ready to be employed in solving current problems in control engineering.

The tutorial is composed of two distinctive parts that review the most important aspects, findings and current trends in both modeling and control applications. The first part offers an introduction to fractional calculus and its numerous applications in the modeling of complex processes. The second part presents the fractional order control applications, both for the single-input-single-output, as well as for the multivariable processes. The final aim of this tutorial is to bring forward advantages and challenges of these emerging tools and raise awarenessin the control engineering community.

T3: L1 Adaptive Control and Its Transition to Practice

Dr. Naira Hovakimyan
Department of Mechanical Science and Engineering
University of Illinois at Urbana-Champaign

Details: Please download the detailed tutorial agenda.

Summary: L1 adaptive control is a powerful tool for controlling systems in the presence of large uncertainties, unmodeled dynamics and disturbances. Its development was motivated by the practical realization problems of model reference adaptive control (MRAC), in which the lack of the transient guarantees and robustness were preventing the transitions to real world problems. The L1 adaptive control theory offers a class of architectures, for which adaptation is decoupled from robustness. The speed of adaptation in these architectures is limited only by the available hardware, while robustness is resolved via conventional methods from classical and robust control. The architectures of L1 adaptive control theory have guaranteed transient performance and guaranteed robustness in the presence of fast adaptation, without introducing or enforcing persistence of excitation, without any gain scheduling in the controller parameters, and without resorting to high--gain feedback. With L1 adaptive controller in the feedback loop, the response of the closed--loop system can be predicted a priori, thus significantly reducing the amount of Monte--Carlo analysis required for verification and validation of such systems. These features of L1 adaptive control theory were verified - consistently with the theory - in a large number of flight tests and in mid--to--high fidelity simulation environments.

This tutorial will give an overview of L1 adaptive control principles, summarize the main results and discuss the transitions. Flight tests of a subscale commercial jet at NASA will illustrate the theoretical findings.

T4: UAV Autonomy and State-of-the-art Technologies and Applications in Mediterranean Countries

Dr. George J Vachtsevanos
Professor Emeritus
Georgia Institute of Technology

Dr. Kimon P. Valanvanis
Professor, ECE
University of Denver

Details: Please download the detailed tutorial agenda.

Workshop Summary: Autonomy, in the context of an integrated system (unmanned system, spacecraft, aircraft, etc.) is the capability of the system to operate independently from external control. Autonomy is also related to system functionality and capabilities, and as such, there are levels of autonomy in a system from basic automation (mechanistic execution of action or response to stimuli) through partial autonomy, flexible autonomy and fully autonomous systems, which are capable of acting independently in dynamic and uncertain environments.

UAVs are playing an increasingly important role in civilian/public domain applications such as forest protection, early fire detection, search and rescue, emergency response, surveillance and reconnaissance, traffic monitoring, crime prevention, infrastructure inspection, environmental monitoring and border patrol, to name but several potential applications.

Focusing on European Union (EU) in general and on Mediterranean countries in particular, UAV research and development has produced remarkable results and UAV systems are currently demonstrating applicability and utilization for diverse applications. Funding from the EU has also contributed to the advancement of the field.

This workshop is aiming at bringing together representative groups to discuss cutting edge UAV technologies and their implementation on specific applications, demonstrating the tools for navigation/control and improved system autonomy. The Workshop will include presentations from the different groups, followed by a panel discussion on challenging issues preventing full utilization of UAVs in civilian domains.

The Workshop is suitable for scientists, engineers and practitioners involved in R&D in the area of complex and/or unmanned systems.