Abstract: There has been remarkable progress in sampled-data control theory in the last two decades. The main achievement here is that there exists a digital (discrete-time) control law that takes the intersample behavior into account and makes the overall analog (continuous-time) performance optimal, in the sense of H-infinity norm. This naturally suggests its application to digital signal processing where the same hybrid nature of analog and digital is always prevalent. A crucial observation here is that the perfect band-limiting hypothesis, widely accepted in signal processing, is often inadequate for many practical situations. In practice, the original analog signals (sounds, images, etc.) are neither fully band-limited nor even close to be band-limited in the current processing standards.
   The present talk describes how sampled-data control theory can be applied to reconstruct the lost high-frequency components beyond the so-called Nyquist frequency, and how this new method can surpass the existing signal processing paradigm. We will also review some concrete examples for sound processing, recovery of high frequency components for MP3/AAC compressed audio signals, and super resolution for image (still/moving) processing. We will also review some crucial steps in leading this technology to the commercial success of 40 million sound processing chips.

Biography: Yutaka Yamamoto received his B. S. and M. S. degrees in engineering from Kyoto University, Kyoto, Japan in 1972 and 1974, respectively, and the M. S. and Ph. D. degrees in mathematics from the University of Florida, in 1976 and 1978, respectively. From 1978 to 1987 he was with Department of Applied Mathematics and Physics, Kyoto University. In 1987 he joined the Department of Applied Systems Science as an Associate Professor, and became a professor in 1997. He is currently a professor at the Department of Applied Analysis and Complex Dynamical Systems, Graduate School of Informatics of Kyoto University.
   His research and teaching interests are in realization and robust control of distributed parameter systems, learning control systems, and sampled-data systems, its application to digital signal processing, with emphasis on sound and image processing.
   Dr. Yamamoto received Sawaragi memorial paper award in 1985, outstanding paper award of SICE in 1987 and in 1997, the best author award of SICE in 1990 and in 2000, the George S. Axelby Outstanding Paper Award in 1996, and the Commendation for Science and Technology by the Minister of Education, Culture, Sports, Science and Technology Prizes for Science of Technology in 2007. He received the IEEE Control Systems Society Distinguished Member Award in 2009, and the Transition to Practice Award of the Control Systems Society in 2012, as well as the ISCIE Best Industrial Paper Award in 2009.
   He is a Fellow of the IFAC, IEEE and SICE.
   He is past President of the IEEE Control Systems Society. He served as vice President for Technical Activities of the CSS for 2005-2006, and as vice President for Publication Activities for 2007-2008. He served as an associate editor of the IEEE Transactions on Automatic Control, Automatica, Systems and Control Letters, and Mathematics of Control, Signals and Systems. He has served as a Senior Editor for the IEEE Transactions on Automatic Control for 2010-2011.
He also served as an organizing committee member of 35th CDC in 1996, MTNS '91 in Kobe, and as a member of program committees of several CDC's. He was the chair of the Steering Committee of MTNS, served as General Chair of MTNS 2006. He was a past President of ISCIE of Japan.

Abstract: A fundamental issue in complex systems theory is to understand how locally interacting agents (or particles) leads to global behaviors (or structures) of the systems. Such problems arise naturally from diverse fields ranging from material and life sciences to social and engineering systems, and have attracted much research attention in recent years. In this lecture, we will first consider synchronization problem of a basic class of non-equillibrium multi-agent systems (or flocks) with local interactions, and show how the required connectivity can be established and how small the interactions radius can be in order to ensure synchronization. Then, we will show how the global behaviors of the flocks may be intervened by using the “soft control” idea, without changing the existing interaction rules of the agents. Finally, we will consider estimation problems of time-varying parameters or adaptive filtering problems, and will show how locally or partially interacting estimators will reached consensus for the estimation problem, which cannot be accomplished by any single estimator due to lack of information. Our results will be established based on analyses of the nonlinear dynamical equations involved and of the asymptotical properties of the spectrum of random geometric graphs.

Biography: Lei GUO received his B.S. degree in mathematics from Shandong University in 1982, and Ph.D. degree in control theory from the Chinese Academy of Sciences (CAS) in 1987. He was a postdoctoral fellow at the Australian National University (1987-1989). Since 1992, he has been a Professor of the Institute of Systems Science at CAS. He has been the President of the Academy of Mathematics and Systems Science, CAS (2003-2012), and is currently the Director of the National Center for Mathematics and Interdisciplinary Sciences, CAS.
   Dr. Guo is a Fellow of IEEE, Member of the Chinese Academy of Sciences, Fellow of the Academy of Sciences for the Developing World (TWAS), Foreign Member of the Royal Swedish Academy of Engineering Sciences, and Fellow of IFAC. He has served as a Council Member of IFAC, Member of IEEE Control Systems Award Committee, Associate Editor of SIAM J. Control and Optimization and Systems and Control Letters, General Co-Chair of the 48th IEEE-CDC, and Vice-Presidents of both Chinese Mathematical Society and Chinese Association of Automation. Currently, he serves as the President of the China Society for Industrial and Applied Mathematics (CSIAM), Congress Director of the 8th International Congress on Industrial and Applied Mathematics, an IEEE CSS Distinguished Lecturer，and on the editorial boards of a number of journals in mathematics, systems and control.
   He has worked on problems in adaptive control, system identification, adaptive signal processing, and time series analysis. His current research interests include the capability of feedback, multi-agent systems, complex adaptive systems, and quantum control systems, among others.

Abstract: Imagine that one day, you have a third arm and a third leg attached to your body. The extra limbs will help you hold objects, support your body, share a workload, and streamline the execution of a task. If the movements of such extra limbs, called Supernumerary Robotic Limbs (SRL), are tightly coordinated with your own arms, you may come to perceive the extra limbs as an extension of your body, incorporated into your body image. The objective of this talk is to address technical challenges for transforming robots to act as parts of a human body. Wearable SRLs are opening up new horizons of robotics, posing diverse research issues and challenges ranging from machine design and human-robot coordination, to biomechanics, motor control, and machine learning and perception.
   Three types of Supernumerary Robotic Limbs being built at the d’Arbeloff Lab of MIT will be presented: 1) a lightweight robot sitting on the shoulder of a human for lifting and supporting objects in the overhead area, 2) a seven-fingered hand (5 fingers + 2 robotic fingers) for grasping and manipulating large/odd-shaped objects, and 3) a pair of wearable canes attached around the waist for supporting and bracing the human body. For these wearable robots, communication and coordination with the human is the key challenge. Three aspects of coordination control will be presented. First, the concept of biological synergies is applied to the seven-fingered hand in order to control the two robotic fingers in concert with the five human fingers. Through grasp experiments and data analysis using Principal Component Analysis it will be shown that synergies exist for seven-fingered hands as well as for five-fingered hands. For real-time control, Partial Least Squares (PLS) regression is used for extracting control laws from the data that can best correlate the posture of the two robotic fingers to that of the five human fingers. Second, interactive human-robot-task processes are modeled as a concurrent, distributed event system based on Coloured Petri Net (CPN). A type of hybrid control system is constructed by replacing CPN’s static state transitions with dynamic, proactive transition laws learned from human demonstration data. Finally, a learning algorithm inspired by biological muscle training is applied to the wearable canes. Untrained robotic actuators are treated as un-innervated muscles. Repeated exposures to simultaneous physical and informational stimulations lead to formation of artificial neuromuscular junctions that control the wearable robots. The seminar will be concluded with potentials of wearable SRLs and their social and economic impacts, ranging from increasing productivity and safety for factory, construction, and field workers to improved quality of life for elderly people and the handicapped as well as reduced workload for caregivers and clinicians.

Biography: H. Harry Asada is Ford Professor of Mechanical Engineering and Director of the Brit and Alex d’Arbeloff Laboratory for Information Systems and Technology in the Department of Mechanical Engineering, Massachusetts Institute of Technology (MIT), Cambridge, MA. He received the B.S., M.S., and Ph.D. degrees in precision engineering in 1973, 1975, and 1979, respectively, all from Kyoto University, Japan. He specializes in robotics, biological engineering, and system dynamics and control. His current robotics research includes wearable robots, cellular PZT actuators, and robot applications to aircraft manufacturing and nuclear power plant monitoring. His research in the bio area focuses on bio-integrated robots, where live cells and tissues are used as components. He received Best Paper Awards at the IEEE International Conference on Robotics and Automation in 1993, 1997, 1999, and 2010, the O. Hugo Schuck Best Paper Award from the American Control Council in 1985, Best Journal Paper Awards from the Society of Instrument and Control Engineers in 1979, 1984, and 1990, and the Best Journal Paper Award from the Journal of Advanced Robotics in 2002. He was the recipient of the Henry Paynter Outstanding Researcher Award from ASME Dynamic Systems and Control in 1998. More recently he received the 2011 Rufus Oldenburger Medal from ASME, and Ruth and Joel Spira Award for Distinguished Teaching from the School of Engineering, MIT. Dr. Asada is a Fellow of ASME.

Abstract: With the vision of the Smart Factory of the future, the manufacturing industries are currently undergoing a fundamental new orientation on the basis of the Cyber-Physical Systems and Internet of Things and Services paradigms. All parts along the manufacturing chain are nowadays equipped with embedded computing, communication and networking capabilities and are expected to interact in an optimal way towards the goal of an energy and resource efficient, save and reliable production process. Through decentralized optimal decision-making and an appropriate communication among the networked individual parts, the whole production process of the future is expected to operate optimally.
   In this presentation an introduction to the goals and principles of Industry 4.0 is given and its challenges and opportunities for the field of automatic control are discussed. We will in particular investigate the potential impact of the field of optimization-based control for the fourth industrial revolution and will present two promising approaches, namely economic model predictive control and distributed, cooperative optimization and control.
Economic model predictive control (MPC) is a control technique which is based on the repeated online solution of an optimal control problem. Contrary to classical MPC, the employed cost function can be some general performance measure, possibly connected to the economics of the considered process. This allows to also consider control objectives different from the classical ones of stabilization or tracking, which makes economic MPC well suited as a tool to achieve the goals of Industry 4.0. In this talk, we examine conditions to classify the optimal operational regime for a system, and propose economic MPC schemes which allow for closed-loop average performance guarantees and satisfaction of (standard pointwise-in-time as well as averaged) constraints.
   For the visions of Industry 4.0 to become reality, tools and methods are required to handle control and decision problems in a distributed and networked fashion. Relating to ideas such as the Internet of Things, distributed optimization algorithms, that work within asynchronous communication networks, are becoming more and more relevant. We present in this talk a broad framework for distributed optimization, in asynchronous peer-to-peer networks. Our framework is based on polyhedral approximations, and lends itself into a variety of distributed algorithms for solving specific decision problem, that are relevant in the context of Industry 4.0. We show how from the general framework algorithms can be derived to solve, e.g., assignment problems or robust optimization problems. Furthermore, we show that the general optimization framework leads naturally to a distributed model predictive control scheme, that is based on the exchange of predicted systems trajectories.

Biography: Frank Allgöwer is director of the Institute for Systems Theory and Automatic Control and full professor in Mechanical Engineering at the University of Stuttgart in Germany. Frank's main interests in research and teaching are in the area of systems and control with emphasis on the development of new methods for optimization-based control, networks of systems and systems biology.
   Frank received several recognitions for his work including the IFAC Outstanding Service Award, the State Teaching Award of the state of Baden-Württemberg, the Leibniz Prize of the Deutsche Forschungsgemeinschaft and several best paper awards.
   At present Frank serves as IEEE CSS Vice-President for Technical Activities and is President-elect of the International Federation of Automatic Control. He is Editor for the journal Automatica and for the Springer Lecture Notes in Control and Information Science book series and serves as Associate Editor or on the editorial board of several further journals. Frank has been organizer or co-organizer of more than a dozen international conferences and has published over 200 scientific articles.
   Since 2012 Frank serves a Vice-President of the German Research Foundation (DFG).

Abstract: Our objective at Berkeley is to create a set of advanced technologies that form the framework for developing accessible exoskeleton systems for people with mobility disorders. Our research work is not about creating “walking” capability only; it is about fostering “independence”. In addition to walking, there are many maneuvers a person with limited mobility needs to carry out for independence at home and work during a day. For widespread use, exoskeletons must be accessible. The medical wearable robotic exoskeletons allow people with paraplegia or other mobility disorders to be upright and mobile, preventing secondary diseases and enhancing their quality of life. These systems will be used for in-home care and everyday use, as well as within hospitals and rehabilitation centers. The industrial wearable robotic systems minimize spinal compression forces of workers who repeat various maneuvers on the job. These devices will be used in auto assembly plants, factories, manufacturing facilities, distribution centers, warehouses, and delivery services. These systems decrease the severity and number of work-related injuries, while enhancing worker safety. The quest to develop accessible exoskeleton orthotic systems suggests less hardware while placing more emphasis on the intelligence and cleverness during both the design stage and the device operation. This talk will describe new engineering developments to realize accessible exoskeleton systems.

Biography: Dr. Kazerooni is a Professor in the Mechanical Engineering Department at the University of California, Berkeley and director of the Berkeley Robotics and Human Engineering Laboratory. The laboratory’s mission is to develop fundamental scientific and engineering principles on robotics, control sciences, exoskeletons, and bioengineering. Dr. Kazerooni is also the founder of Ekso Bionics. Most of the developed technologies in this lab have found their ways to market. Prior to his research work on lower extremity exoskeletons, Dr. Kazerooni led his team to successfully develop robotics systems that enhance human upper extremity strength. The results of this work led to a new class of intelligent assist devices currently being used by workers worldwide for manipulating heavy objects in distribution centers and factories. Dr. Kazerooni holds a Doctorate in Mechanical Engineering from MIT and has published more than two hundred articles, delivered over 100 plenary lectures in the U.S. and internationally, and holds numerous pertinent patents and awards. As a noted authority on robotics, he is frequently profiled and quoted in the media. More information can be obtained in http://en.wikipedia.org/wiki/Homayoon_Kazerooni

Abstract: Recently, numerous studies on small unmanned aerial vehicles (UAVs) are conducted with various practical usages. Transportation of a payload is one of the missions that can be implemented in military or civilian operations. In this talk, some important aspects of modeling and control design of multi-UAV transportation system is discussed.
   System dynamic modeling is heavily dependent on the type of the transportation. One option is the string-based transportation called the slung-load transportation, and other method is called the body-contact transportation. For the slung-load transportation, a payload is tied to a set of strings that are connected to each transporting UAV. The major advantage of this method is that the rotational motion of each UAV can be decoupled from the motion of the payload and other UAV’s. On the other hand, the body-contact transportation type is to directly attach the body of the UAVs to the payload, so that there is no need for a string. However, the motion of the UAV’s is constrained since the UAV’s are rigidly attached to the payload.
   The equations of motion can be derived by several modeling methods. Specifically, Udwadia-Kalaba Equation (UKE) is very useful in modeling constrained systems such as the slung-load transportation systems. However, obtaining a minimal state-space representation from this approach is not so easy. A Newtonian approach with a judicious choice of coordinates system may be a better strategy.
   Recognizing the payload is also an important task. An onboard camera may detect a QR code market attached to the payload to identify the payload and obtain extra information such as the weight of the payload and the location of the grip points. This information helps to determine the required number of UAV’s
   Variations in payload weight should be considered in control design. Since the slung-load system is a coupled system with different dynamic entities, the system can easily become unstable. Robust controllers such as LQG/LTR and PRLQG(parameter robust LQG) can provide stability and performance robustness. The performance of the controllers can be compared by computer simulation or indoor flight tests. Motion capture systems with multiple cameras are valuable tools for this purpose.

Biography: Dr. Tahk is Professor in Aerospace Engineering at Korea Advanced Institute of Sciene and Technology(KAIST). He received the B.S. degree in aeronautical engineering from Seoul National University in 1976, and the M.S. and Ph.D. degrees in aerospace engineering from the University of Texas at Austin in 1983 and 1986, respectively.
   Before he joind KAIST in 1989, he worked for Agency for Defense Development, Daejeon Korea, from 1976 to 1981, and Integrated Systems Inc., Santa Clara CA, USA, from 1987 to 1989. He has served various academic institutes: Vice President of ICROS in 2007-2008 and 2010, President of the Korean Society for Aeronautical & Space Sciences(KSAS) in 2012, and President of Korea Unmanned Vehicle Systems Association(KUVSA) in 2013-2014.
   He was also the IPC Co-Chair of the 60th International Astronautical Congress(IAC) held in Dajeon, Korea, in 2009. Now his editorial duties include Technical Editor for Guidance and Control, IEEE Tr. Aerospace and Electronic Systems. His major research area is guidance and control of missile and UAV systems, target tracking and collision avoidance, and parameter optimization techniques. He has published 180 papers in international and domestic journals and presneted more than 400 conference papers.