Kazuyuki Aihara (The University of Tokyo, Japan)
Nonlinear Dynamics and Spatio-Temporal Patterns with Possible Functions in Networked Systems
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 , dynamical network biomarkers , and hierarchical circadian dynamics in Arabidopsis .
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
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).
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).
Lei Guo (Academy of Mathematics and Systems Science, China)
Distributed Adaptive Filtering
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
We examine two problems of contemporary interest, both involving the optimal operation of
distributed stochastic dynamic systems, one in power systems and another in
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.
Luca Schenato (University of Padova, Italy)
Multi-agent Map-building over Lossy Networks: From Parametric to
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.
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.
Misako Takayasu (Tokyo Institute of Technology, Japan)
Instability of Nationwide Business Transaction Network
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.
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
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.
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
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.
Plenary talks 6 and 9 are supported by Grant-in-Aid for Scientific Research (A) 25249058.