Plenary Speakers

Kazuyuki Aihara (The University of Tokyo, Japan)

Nonlinear Dynamics and Spatio-Temporal Patterns with Possible Functions in Networked Systems

Abstract: Nonlinear dynamics of networked systems generates various spatio-temporal patterns with possible functions. In this talk, I explain our recent works on nonlinear dynamics and spatio-temporal patterns in networked systems such as chaotic and quantum artificial neural networks [1], dynamical network biomarkers [2], and hierarchical circadian dynamics in Arabidopsis [3].

References:
[1] K. Aihara and M. Hasegawa: "Optimization, Chaotic Neural Networks, and Coherent Ising Machines," Proceedings of the IEEE, Vol.102, No.4, p.585 (2014).
[2] R. Liu, M. Li, Z.-P. Liu, J. Wu, L. Chen, and K. Aihara: "Identifying Critical Transitions and their Leading Biomolecular Networks in Complex Diseases," Scientific Reports, Vol.2, Article No.813, pp.1-9 (2012).
[3] N. Takahashi, Y. Hirata, K. Aihara, and P. Mas: "A Hierarchical Multi-oscillator Network Orchestrates the Arabidopsis Circadian System," Cell, Vol.163, No.1, pp.148-159 (2015).

Short Bio: Kazuyuki Aihara received the B.E. degree of electrical engineering in 1977 and the Ph.D. degree of electronic engineering 1982 from the University of Tokyo, Japan. Currently, he is Professor of Institute of Industrial Science, Professor of Graduate School of Information Science and Technology, Professor of Graduate School of Engineering, and Director of Collaborative Research Center for Innovative Mathematical Modelling at the University of Tokyo. His research interests include mathematical modeling of complex systems, chaotic and quantum neural networks, and time series analysis of complex data.

Brian D. O. Anderson (Hangzhou Dianzi University, China, Australian National University, Canberra, Australia, Data61 CSIRO, Australia)

Localization of Airborne Vehicles in a GPS-Denied Environment
(Slides)

Abstract: When unmanned airborne vehicles are performing surveillance, it is obviously important to be able to localize their position, and when multiple vehicles are operating in a formation, the maintenance of a correct formation shape demands an ability for the vehicles to be able to localize each other. However a major problem is that GPS is not always available, because of in-building operation (for microvehicles), 'building canyon' operation in cities, or active denial (for conventional UAVs).
    Initially the problem is considered as to how one GPS-equipped vehicle can localize in a three-dimensional ambient space a second GPS-denied vehicle using knowledge of its own motion, of the inter-vehicle distances at a series of points in time, and of the motion of the GPS-denied vehicle specified in local coordinates associated with that vehicle, derived from an inertial navigation system on the vehicle. The INS system provides consistent measurements over a short period, but loses it absolute reference due to drift. Critically also, inter-vehicle bearings are not available.
    Complicating features include the presence of substantial noise on the inter-vehicle distance measurements, but effective algorithms can be obtained, based on a combination of semidefinite programming and maximum likelihood estimation, and these have been validated with real flight data.
    Extension of the results to multi-vehicle situations is also considered. This involves concepts from rigidity theory applied to body-bar frameworks.

Short Bio: Brian D. O. Anderson was born in Sydney, Australia, and educated at Sydney University in mathematics and electrical engineering, with PhD in electrical engineering from Stanford University in 1966. Following graduation, he joined the faculty at Stanford University and worked as Vidar Corporation of Mountain View, California, as a staff consultant. He then returned to Australia to become a department chair in electrical engineering at the University of Newcastle. From there, he moved to the Australian National University in 1982, as the first engineering professor at that university. He became an emeritus professor at ANU in July 2016 and Distinguished Professor at Hangzhou Dianzi University, and a Distinguished Researcher in Data 61 CSIRO (previously NICTA).
    During his period in academia, he spent significant time working for the Australian Government, with this service including membership of the Prime Minister's Science Council under the chairmanship of three prime ministers. He also served on advisory boards or boards of various companies, including the board of the world's major supplier of cochlear implants, Cochlear Corporation, where he was a director for ten years.
    His awards include the IFAC Quazza Medal in 1999, IEEE Control Systems Award of 1997, the 2001 IEEE James H Mulligan, Jr Education Medal, and the Bode Prize of the IEEE Control System Society in 1992, as well as IEEE and other best paper prizes, including Automatica. He is a Fellow of the Australian Academy of Science, Australian Academy of Technological Sciences and Engineering, Royal Society (London), and a foreign member of the US National Academy of Engineering. He holds honorary doctorates from a number of universities, including Universite Catholique de Louvain, Belgium, and ETH, Zurich.
    He served as IFAC President from 1990 to 1993, having had earlier periods in various IFAC roles, including editor of Automatica. He was also President of the Australian Academy of Science from 1998 to 2002. His current research interests are in distributed control, sensor networks and econometric modelling.

Lei Guo (Academy of Mathematics and Systems Science, China)

Distributed Adaptive Filtering
(Slides)

Abstract: Distributed adaptive filtering can estimate a dynamic process of interest by a set of sensors working cooperatively, even when any individual sensor cannot fulfill the estimation task due to lack of necessary signal information. In this lecture, we will present a theory on stability and performance analysis for a class of least mean square (LMS) based distributed filtering algorithms with non-vanishing gains. A general stochastic cooperative information condition will be introduced to guarantee the stability of this kind of distributed algorithms, without resorting to such commonly used stringent conditions as independency and stationarity in the existing literature, and thus makes the adaptive filtering theory applicable to stochastic systems with feedback. Moreover, this cooperative information condition will be shown to be not only sufficient but also necessary for stability of the distributed filtering algorithm for a large class of random signals with decaying dependency. We will further show that the filtering error covariance matrix can be approximately calculated by a linear deterministic difference matrix equation that can be easily evaluated, analyzed and even optimized.

Short Bio: Lei GUO is a Professor at the Academy of Mathematics and Systems Science, Chinese Academy of Sciences (CAS), and Director of the National Center for Mathematics and Interdisciplinary Sciences, CAS. He has worked on problems in adaptive control, system identification, adaptive signal processing, and stochastic systems. His current research interests include distributed estimation, multi-agent systems, capability of feedback, game-based control systems, and quantum control systems. Dr. Guo is a Fellow of IEEE, Fellow of IFAC, Member of CAS, Fellow of the Academy of Sciences for the Developing World (TWAS), and a Foreign Member of the Royal Swedish Academy of Engineering Sciences. He has been a Council Member of IFAC, and currently serves as the President of the China Society for Industrial and Applied Mathematics (CSIAM), among others.

Shinji Hara (University of Tokyo, Japan)

Hierarchical Decentralized Control for Networked Dynamical Systems: Framework, Theory, and Applications in Biology

Abstract: There are many dynamical systems that can be regarded as hierarchical networked systems in a variety of fields related to worldwide crucial social problems such as environment, energy, transportation, and health. One of the ideas to treat those systems properly is "Glocal Control," which means that the global purpose is achieved by only local actions of measurement and control. The key for realization of glocal control is hierarchical networked dynamical systems with multiple resolutions in time and space depending on the layer. After the explanation of the background, a unified framework for hierarchical networked dynamical systems is introduced. The first part of the control theory is on stability, where three different types of stability tests, namely Nyquist, Hurwitz, and Lyapunov, are shown, and the robust stability issue is discussed for treating the heterogeneous case. We then focus on how to design hierarchical decentralized control with both local and global objectives, where a couple of hierarchical decentralized optimal control synthesis methods are presented. Through the talk we show the effectiveness of the theoretical results for applications of biological systems including gene regulatory networks and biomolecular communication networks by experiments as well as by simulations.

Short Bio: Shinji Hara received the B.S., M.S., and Ph.D. degrees in engineering all from Tokyo Institute of Technology, Tokyo, Japan, in 1974, 1976, and 1981, respectively. In 1984, he joined Tokyo Institute of Technology as an Associate Professor and has served as a Full Professor for ten years. Since 2002 he has been a Full Professor of the Department of Information Physics and Computing, The University of Tokyo. His current research interests are in robust control, decentralized cooperative control for large-scale networked dynamical systems, system biology, glocal control. Dr. Hara received the George S. Axelby Outstanding Paper Award from the IEEE Control System Society in 2006. He was the President of SICE in 2009 and the Vice-President of the IEEE CSS in 2009-2010, IFAC Council member in 2012-, and Fellow of IFAC, IEEE and SICE.

P. R. Kumar (Texas A&M University, USA)

The Prices of Packets and Watts: Optimal Operation of Decentralized Stochastic Systems
(Slides)

Abstract: We examine two problems of contemporary interest, both involving the optimal operation of distributed stochastic dynamic systems, one in power systems and another in communication networks.
    In power systems we address the problem faced by an Independent System Operator which has to optimally utilize a mix of fossil fuel based and renewable generators, controllable and uncontrollable loads, prosumers and storage services, so as to maximize social welfare, without knowing details of any of the entities involved. We revisit general equilibrium theory, addressing the complexity raised by dynamic stochastic agents with privacy concerns. We show how optimality can be attained through stochastic prices discovered by iterative tatonnement mechanisms.
    In communication networks we address the problem of how to optimally schedule multiple flows with hard end-to-end deadlines over a network of unreliable links with average power constraints so as to maximize their throughput. We exhibit an exactly optimal policy for this distributed system that employs easily determined prices to distributedly schedule link transmissions throughput the entire network.
    [Joint work with Rahul Singh and Le Xie]

Short Bio: P. R. Kumar obtained his B. Tech. degree in Electrical Engineering (Electronics) from I.I.T. Madras in 1973, and the M.S. and D.Sc. degrees in Systems Science and Mathematics from Washington University, St. Louis, in 1975 and 1977, respectively. From 1977-84 he was a faculty member in the Department of Mathematics at the University of Maryland Baltimore County. From 1985-2011 he was a faculty member in the Department of Electrical and Computer Engineering and the Coordinated Science Laboratory at the University of Illinois. Currently he is at Texas A&M University, where he is a University Distinguished Professor and holds the College of Engineering Chair in Computer Engineering.
    Kumar has worked on problems in game theory, adaptive control, stochastic systems, simulated annealing, neural networks, machine learning, queueing networks, manufacturing systems, scheduling, wafer fabrication plants and information theory. His research is currently focused on energy systems, wireless networks, secure networking, automated transportation, and cyberphysical systems.
    Kumar is a member of the National Academy of Engineering of the USA, and a Fellow of the World Academy of Sciences. He was awarded an honorary doctorate by the Swiss Federal Institute of Technology (Eidgenossische Technische Hochschule) in Zurich. He received the Outstanding Contribution Award of ACM SIGMOBILE, the IEEE Field Award for Control Systems, the Donald P. Eckman Award of the American Automatic Control Council, and the Fred W. Ellersick Prize of the IEEE Communications Society. He is an ACM Fellow and a Fellow of IEEE. He was a Guest Chair Professor and Leader of the Guest Chair Professor Group on Wireless Communication and Networking at Tsinghua University, Beijing, China. He is an Honorary Professor at IIT Hyderabad. He is a D. J. Gandhi Distinguished Visiting Professor at IIT Bombay. He was awarded the Distinguished Alumnus Award from IIT Madras, the Alumni Achievement Award from Washington University in St. Louis, and the Daniel C. Drucker Eminent Faculty Award from the College of Engineering at the University of Illinois.

Luca Schenato (University of Padova, Italy)

Multi-agent Map-building over Lossy Networks: From Parametric to Non-parametric Approaches
(Slides)

Abstract: The proliferation of large scale smart multi-agent systems, also known as Internet-of-Things, Networked Control Systems, Wireless sensor and actuator networks, Cyber-physical Systems, etc., are providing us with a wealth of data with unprecedented time-space resolution which can trigger the next technological revolution. However, this trend is also posing a formidable challenge, often referred as Data Tsunami, which requires the analysis of a large scale correlated time-series. Moreover, data is transmitted over a shared medium (wireless, Internet, etc..) which causes packet losses and random delays. In this talk, I will address the problem of estimating a map based on noisy measurements collected by a large number of sensors in the presence of unreliable communication. I will explore this problem by looking at different design choices: centralized vs distributed estimation, parametric vs non-parametric modeling of the underlying map, static vs time-varying maps, and static vs mobile agents. Particular emphasis will be placed on open problems and current research trends.

Short Bio: Luca Schenato received the Dr. Eng. degree in electrical engineering from the University of Padova in 1999 and the Ph.D. degree in Electrical Engineering and Computer Sciences from the UC Berkeley, in 2003. He held a post-doctoral position in 2004 and a Visiting Professor position in 2013-2014 at U.C. Berkeley. Currently he is Associate Professor at the Information Engineering Department at the University of Padova. His interests include networked control systems, multi-agent systems, cyber-physical systems, smart grids and cooperative robotics. Luca Schenato has been awarded the 2004 Researchers Mobility Fellowship by the Italian Ministry of Education, University and Research (MIUR), the 2004 Marie Curie International Reintegration Grant, the 2006 Eli Jury Award in U.C. Berkeley, and the EUCA European Control Award in 2014. He served as Associate Editor for IEEE Trans. on Automatic Control (2010 to 2014) and IEEE Trans. on Control of Network Systems (2016-current), and he is Senior Member of IEEE.
URL: http://automatica.dei.unipd.it/people/schenato.html

Misako Takayasu (Tokyo Institute of Technology, Japan)

Instability of Nationwide Business Transaction Network

Abstract: Dynamical transport on complex network in social activities has been attracting much attention. We report the stability of nationwide business transaction network consists of 1 million firms with 5 million transactions observed for sucssesive10 years. In the first part, we show the statistical properties observed from the data, and derive a set of nonlinear transport equations for the money flow on the network. We also introduce a minimal stochastic model of network evolution which satisfies the empirical laws for the network structure. In the latter part, we show the simulation results of our network model and discuss about the stability of the system depending on the parameters.

References:
[1] Wataru Miura, Hideki Takayasu, and Misako Takayasu, "Effect of coagulation of nodes in an evolving complex network", Physical Review Letters 108, 16, 168701 (2012)
[2] Hayafumi Watanabe, Hideki Takayasu, and Misako Takayasu, "Biased diffusion on Japanese inter-firm trading network", New Journal of Physics 14, 10, 043034 (2012)
[3] Koutarou Tamura, Wataru Miura, Misako Takayasu, Hideki Takayasu, Satoshi Kitajima , Hayato Goto, "Estimation of flux between interacting nodes on huge inter-firm networks", International Journal of Modern Physics: Conference Series 16, 93 (2012)

Short Bio: Misako Takayasu received the B.E. degree of physics from Nagoya University, and Ph.D. degree in Material Science from Kobe University. She is a Research Leader of Advanced Data Analysis and Modeling Unit, Associate Professor in Institute of Innovative Research, Tokyo Institute of Technology. Her research interest covers wide fields of science including financial systems, traffic systems and biological systems.

Wing Shing Wong (Chinese University of Hong Kong, China)

From Control of Networks to Networked Control
(Slides)

Abstract: Data center networks (DCNs) play an increasingly crucial role in today's Internet. Due to the unprecedented growth in data traffic demands, scalability is an important issue to address. Many scalable DCN architectures have been proposed, among them fat-tree, which is essentially a folded version of a Clos network, is gaining popularity. A DCN adopting a fat-tree structure can host up to millions of servers, which raises interesting challenges for network control. Another important trend in the Internet is Software-Defined Networking, which allows easier and more open access to switches and routers in a DCN by user applications.
    This talk will start with some network control problems we have been analyzing for fat-tree based DCNs, including routing, scheduling and load balancing problems. We will further explain how these Internet developments will likely make impacts on networked control.

Short Bio: Wong Wing Shing is an IEEE Fellow, a Fellow of the HKIE, and a Fellow of the Hong Kong Academy of Engineering Sciences. He was recruited by the AT&T Bell Laboratories in 1982 and was subsequently promoted to a group supervisor. He joined the Chinese University of Hong Kong in 1992, was promoted to a Professor of Information Engineering in 1996, and served as the Chairman of the Information Engineering Department from 1995 to 2003. He served as the Science Advisor at the Innovation and Technology Commission of the Hong Kong SAR Government from 2003 to 2005. He served as the Dean of the Graduate School from 2005 to 2014. He was a Board Director of the Hong Kong Applied Science and Technology Research Institute and is currently a Board Director of the Hong Kong Science and Technology Parks Corporation and the Nano and Advanced Materials Institute Limited. His research interests include information-based control and wireless communication.

Lihua Xie (Nanyang Technological University, Singapore)

Existence, Convergence and Efficiency Analysis of Nash Equilibrium and Its Application to Traffic Networks
(Slides)

Abstract: This talk will discuss existence, convergence and efficiency analysis of Nash equilibrium in variety classes of games and their applications in traffic networks. We shall first discuss the trip timing problem where potential game and distributed consensus are introduced to solve this non-cooperative congestion game. The convergence of Nash equilibrium is established and dynamic road pricing is applied to mitigate the traffic congestion. Next, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA), which is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow, in a traffic network where each edge in the network is associated with a latency function. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. Simulations with real traffic data are presented to illustrate the results.

Short Bio: Lihua Xie received the B.E. and M.E. degrees in electrical engineering from Nanjing University of Science and Technology in 1983 and 1986, respectively, and the Ph.D. degree in electrical engineering from the University of Newcastle, Australia, in 1992. He was with the Department of Automatic Control, Nanjing University of Science and Technology from 1986 to 1989. Since 1992, he has been with the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, where he is currently a professor and the Director of the Delta-NTU Corporate Laboratory on Cyber-Physical Systems. He served as the Head of Division of Control and Instrumentation from July 2011 to June 2014, and the Director, Centre for E-City from July 2011 to June 2013. He is Fellow of IEEE and Fellow of IFAC.