Speaker: Professor Tianyou Chai
Northeastern University, Shenyang, China

Tianyou Chai received the Ph.D. degree in control theory and engineering in 1985 from Northeastern University, Shenyang, China, where he became a Professor in 1988. He is the founder and Director of the Center of Automation, which became a National Engineering and Technology Research Center and a State Key Laboratory. He is a member of Chinese Academy of Engineering, IFAC Fellow and IEEE Fellow, director of Department of Information Science of National Natural Science Foundation of China. His current research interests include modeling, control, optimization and integrated automation of complex industrial processes. 
He has published 170 peer reviewed international journal papers. His paper titled Hybrid intelligent control for optimal operation of shaft furnace roasting process was selected as one of three best papers for the Control Engineering Practice Paper Prize for 2011-2013. He has developed control technologies with applications to various industrial processes. For his contributions, he has won 4 prestigious awards of National Science and Technology Progress and National Technological Innovation, the 2007 Industry Award for Excellence in Transitional Control Research from IEEE Multiple-conference on Systems and Control.

Title: Smart optimization control system for energy-intensive equipment

China has abundance of mineral resources such as magnesite, hematite and bauxite, which constitute a key component of its economy. The relatively low grade, and the widely varying and complex compositions of the raw extracts, however, pose difficult processing challenges including specialized equipment with excessive energy demands. The energy intensive furnaces together with widely uncertain features of the extracts form hybrid complexities of the system, where the existing modeling, optimization and control methods have met only limited success. Currently, the mineral processing plants generally employ manual control and are known to impose greater demands on the energy, while yielding unreasonable waste and poor operational efficiency. The recently developed Cyber-Physical System (CPS) provides a new key for us to address these challenges. The idea is to make the control system of energy intensive equipment into a CPS, which will lead to a smart optimization control system.
This talk presents the syntheses and implementation of a smart optimization control system for energy-intensive equipment under the framework of CPS. The proposed smart optimization control system consists of three main functions: (i) process control; (ii) setpoint optimization control; and (iii) fault diagnosis and self-recovery control. The key in realizing the above functions is the algorithm structure which is able to integrate control, optimization, fault diagnosis and self-recovery control together seamlessly.  This talk introduces the algorithm structure for integrated implementation of setpoint optimization control, process control and fault diagnosis and self-recovery control.
Hardware and software platform of smart optimization control system for energy-intensive equipment is then briefly introduced, which adopts embedded control system, wireless network and industrial cloud. It not only realizes the functions of computer control system using DCS (PLS), optimization computer and fault diagnosis computer, but also achieves the functions of mobile and remote monitoring for industrial process. 
Then, using fused magnesium furnace as an example, a hybrid simulation system for smart optimization control system for energy-intensive equipment developed by our team is introduced. The results of simulation experiments show the effectiveness of the proposed method that integrates the process control, setpoint optimization control and fault diagnosis and self-recovery control in the framework of CPS.
The industrial application of the proposed smart optimization control system is also discussed. It has been successfully applied to the largest magnesia production enterprise in China, resulting in great returns. Finally, future research on the smart optimization control system is outlined.


Witold Pedrycz (IEEE Fellow, 1998) is Professor and Canada Research Chair (CRC) in Computational Intelligence in the Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada. He is also with the Systems Research Institute of the Polish Academy of Sciences, Warsaw, Poland. In 2009 Dr. Pedrycz was elected a foreign member of the Polish Academy of Sciences. In 2012 he was elected a Fellow of the Royal Society of Canada. Witold Pedrycz has been a member of numerous program committees of IEEE conferences in the area of fuzzy sets and neurocomputing. In 2007 he received a prestigious Norbert Wiener award from the IEEE Systems, Man, and Cybernetics Society. He is a recipient of the IEEE Canada Computer Engineering Medal, a Cajastur Prize for Soft Computing from the European Centre for Soft Computing, a Killam Prize, and a Fuzzy Pioneer Award from the IEEE Computational Intelligence Society.

His main research directions involve Computational Intelligence, fuzzy modeling and Granular Computing, knowledge discovery and data science, fuzzy control, pattern recognition, knowledge-based neural networks, relational computing, and Software Engineering. He has published numerous papers in this area. He is also an author of 16 research monographs and edited volumes covering various aspects of Computational Intelligence, data mining, and Software Engineering.

Dr. Pedrycz is vigorously involved in editorial activities. He is an Editor-in-Chief of Information Sciences, Editor-in-Chief of WIREs Data Mining and Knowledge Discovery (Wiley), and Int. J. of Granular Computing (Springer).  He serves on an Advisory Board of IEEE Transactions on Fuzzy Systems and is a member of a number of editorial boards of international journals.

Title: Association Analysis in Data Analytics: Designing Associative Memories-Architectural, Design, and Interpretation Considerations


Association analysis arises as one of the pivotal pursuits in data science-- identifying  relationships among variables, building concepts, and recalling associated entities are central to knowledge discovery.

Associative memories have been studied in the past. In light of the agenda of data analytics, the underlying idea, architectures, and algorithmic developments call for the essential revisiting of the well-established paradigm.

In this talk, we elaborate on the key topologies of associative memories and stress ideas of bidirectional and multi-directional recalls. The architecture of the associative mappings dwells upon a collection of landmarks (prototypes) whose formation is realized with the aid of advanced techniques of collaborative clustering. The detailed clustering algorithm with optimized collaboration coefficients and the ensuing recall mechanisms are discussed.  It is shown that the proposed design retains privacy of individual sources of data for which associations are established.  We demonstrate how the advanced design facets embrace (i) the usage of Granular Computing leading to granular associative memories, and (i) the design of interfaces of deep learning implying further augmentations of association mechanisms.

Speaker: Professor Edwin K. P. Chong [CV]
Dept. of Electrical and Computer Engineering and Dept. of Mathematics, Colorado State University

Edwin K. P. Chong received the B.E. degree with First Class Honors from the University of Adelaide, South Australia, in 1987; and the M.A. and Ph.D. degrees in 1989 and 1991, respectively, both from Princeton University, where he held an IBM Fellowship. He joined the School of Electrical and Computer Engineering at Purdue University in 1991, where he was named a University Faculty Scholar in 1999. Since August 2001, he has been a Professor of Electrical and Computer Engineering and Professor of Mathematics at Colorado State University.  He coauthored the best-selling book, An Introduction to Optimization (4th Edition, Wiley-Interscience, 2013). He received the NSF CAREER Award in 1995 and the ASEE Frederick Emmons Terman Award in 1998. He was a co-recipient of the 2004 Best Paper Award for a paper in the journal Computer Networks. In 2010, he received the IEEE Control Systems Society Distinguished Member Award.
Prof. Chong is a Fellow of IEEE. He was the founding chairman of the IEEE Control Systems Society Technical Committee on Discrete Event Systems, and served as an IEEE Control Systems Society Distinguished Lecturer. He is currently a Senior Editor of the IEEE Transactions on Automatic Control, and has also served on the editorial boards of Computer Networks, Journal of Control Science and Engineering, and IEEE Expert Now. He was the General Chair for the 2011 Joint 50th IEEE Conference on Decision and Control and European Control Conference. He has served as a member of the IEEE Control Systems Society Board of Governors and as Vice President for Financial Activities until 2014. He currently serves as President (2017).

Title: Greedy Strategies and Submodular Optimization

We discuss optimization problems where the objective function is submodular, which roughly means that it has the property of diminishing returns. In such problems, we can provably bound the performance of the greedy solution relative to the optimal solution. We present a variety of recent results related to such optimization problems, including bounds for "string-submodular" problems, bounds related to k-batch greedy strategies, improved bounds involving notions of curvature, and bounds on Nash equilibria in submodular games. We illustrate these results in the context of various application problems arising in task scheduling.

Bernard De Baets is a senior full professor in applied mathematics at the Faculty of Bioscience Engineering of Ghent University, the top-ranked Belgian university (Shanghai-rank 62). He is leading the research unit KERMIT and acts as head of the Department of Mathematical Modelling, Statistics and Bioinformatics. He lectures various courses to hundreds of bachelor and master students. Moreover, he is also an affiliated professor at the Anton de Kom Universiteit (Suriname), an Honorary Professor of Budapest Tech (Hungary) and a Doctor Honoris Causa of the University of Turku (Finland).

As a trained mathematician, computer scientist and knowledge engineer, Bernard has developed a passion for multi- and interdisciplinary research. He is not only deeply involved in fundamental research in three interlaced research threads, namely knowledge-based, predictive and spatio-temporal modelling, but also aims at innovative applications in the applied biological sciences. At present, over 30 researchers are involved in the activities of KERMIT. Over the past 20 years, 61 PhD students have graduated under his (co-)supervision.

Bernard is a prolific writer, with a bibliography comprising well over 400 peer-reviewed journal papers, 60 book chapters and 300 contributions to conference proceedings, accumulating over 15000 Google Scholar citations (h-index 58). Several of his works have been bestowed upon with a best paper award. Moreover, he is a much-invited speaker, having delivered over 200 lectures world-wide. In 2011, he was elected Fellow of IFSA (International Fuzzy Systems Association) and in 2012, he was a nominee for the Ghent University Prometheus Award for Research.

Bernard actively serves the research community, in particular as co-editor-in-chief of Fuzzy Sets and Systems and as member of the editorial board of several other journals, including the Internat. J. of Approximate Reasoning, Engineering Applications of Artificial Intelligence, and the Iranian J. of Fuzzy Systems. Currently, he is vice-president of EUSFLAT (European Society for Fuzzy Logic and Technology) and member of the Administrative Board of the Belgian OR Society.

Title: Towards a new theory of aggregation


The study of aggregation functions is undeniably one of the most important spin-offs of fuzzy set theory. Although the major part of the literature considers the aggregation of numerical values, also qualitative linearly or partially ordered scales are witnessing increased attention. One could say that there is a shift towards the aggregation on structures.

Given the data-generating era we are living in, materialized in the buzzword big data, a dedicated study of aggregation processes has become even more indispensable. This lecture is an appeal to the fuzzy set community to play a key role in this endeavour. This can only be achieved with an open mind. Firstly, although the unifying conditions of aggregation functions (boundary conditions and monotonicity) are extremely basic, we claim that their generality might be questioned. Secondly, the aggregation of structured information, such as rankings, graphs, trees, posets is likely to become a hot topic. 

In short, we expect to see an increasing interest in the aggregation of relational data, just as has been the case already in the closely related field of machine learning. We will focus on the aggregation of rankings, point to largely ignored monotonicity issues and downgrade the role of distance metrics in favour of the recently introduced monometrics, which should be appealing to the fuzzy set community.

In this way we might all work together to achieve aggregation 2.0.

Speaker: Prof. Shigeki Sugano

Shigeki Sugano received the B.S., M.S., and Dr. of Engineering degrees in mechanical engineering in 1981, 1983, and 1989 from Waseda University. From 1987 to 1991, he was a research associate at Waseda University. Since 1991, he has been a faculty member in the Department of Mechanical Engineering at Waseda, where he is currently a professor. From 1993 to 1994, he was a visiting scholar in the Mechanical Engineering Department at Stanford University. From 2001 to 2012, he served as the director of the Waseda WABOT-HOUSE laboratory. Since 2012, he has been the director of the Institute for Techno-Innovation in Chubu-Area Industries. Since 2000, He has been a member of the Humanoid Robotics Institute of Waseda University. From 2011 to 2014, he served as the Associate Dean of the School of Creative Science and Engineering, Waseda University. Since 2014, he has served as the Dean of the School of Creative Science and Engineering, Waseda University. Since 2013, he has served as the Program Coordinator of the MEXT Leading Graduate Program: Waseda Embodiment Informatics Program. 

His research interests include human-symbiotic anthropomorphic robot design, dexterous and safe manipulator design, and human-robot communication. He received the Technical Innovation Award from the Robotics Society Japan for the development of the Waseda Piano-Playing Robot: WABOT-2 in 1991. He received the JSME Medal for Outstanding Paper from the Japan Society of Mechanical Engineers in 2000, the JSME Fellow Award in 2006, and the IEEE Fellow Award in 2007. He also received IEEE RAS Distinguished Service Award in 2008, the RSJ Fellow Award in 2008, and the SICE Fellow Award in 2011.He received RSJ Distinguished Service Award in 2012.

He served as the Secretary of the IEEE Robotics & Automation Society (RAS) in 2006 and 2007. He served as a Co-Chair of the IEEE RAS Technical Committee on Humanoid Robotics from 2005 to 2008. He served as the IEEE RAS Conference Board, Meetings Chair from 1997 to 2005. He served as an AdCom member of the IEEE RAS and the Associate Vice-President of the IEEE RAS Conference Board from 2008 to 2013.

From 2007 to 2012, he served as the Editor in Chief of the International Journal of Advanced Robotics. He served as the Head of the System Integration Division of the Society of Instrument and Control Engineers (SICE) in 2006 and 2007. He serves as a Director of SICE in 2008 and 2009. From 2001 to 2010, he served as the President of the Japan Association for Automation Advancement.

He served as the General Chair of the 2003 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM2003). He was a General Co-Chair of the 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS2006) and a Program Co-Chair of the 2009 IEEE International Conference on Robotics and Automation (ICRA2009). He served as the General Chair of the SICE2011 in 2011. He also served as the General Co-Chair of the 2012 IEEE International Conference on Robotics and Automation (ICRA2012), the Program Chair of the 2012 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM2012) and the General Chair of the 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS2013) in Tokyo.

Speech title: Intelligent Human-Symbiotic Robot as a Cyber-Physical-System in Society5.0

IoT technologies such as CPS, Industry4.0, Industrial Internet and Society5.0 are important concepts in designing and building future social systems. Intelligent Human-Symbiotic Robot is a typical example of IoT technologies. In this speech, first, I introduce Society 5.0 by Japanese government and its concepts. And I show several approaches to realize intelligent human-robot systems based on that concepts. In designing interface for human-robot system, both computational intelligence and mechanical design are important key technologies. Both of them have advantages and disadvantages. Computational intelligence realizes universal adaptability, and special mechanical design realizes ideal specifications and low cost. Both approaches should be merged together to realize an intelligent human-symbiotic robot. I call its approach "Embodiment Informatics". I will introduce several research topics in Embodiment Informatics.

Speaker : Professor Zongli Lin 
University of Virginia

Zongli Lin is the Ferman W. Perry Professor in the School of Engineering and Applied Science and a professor of Electrical and Computer Engineering at University of Virginia. He received his B.S. degree in mathematics and computer science from Xiamen University, Xiamen, China, in 1983, his Master of Engineering degree in automatic control from Chinese Academy of Space Technology, Beijing, China, in 1989, and his Ph.D. degree in electrical and computer engineering from Washington State University, Pullman, Washington, in 1994. His current research interests include nonlinear control, robust control, and control applications. He was an Associate Editor of the IEEE Transactions on Automatic Control (2001-2003), IEEE/ASME Transactions on Mechatronics (2006-2009) and IEEE Control Systems Magazine (2005-2012). He was an elected member of the Board of Governors of the IEEE Control Systems Society (2008-2010) and chaired the IEEE Control Systems Society Technical Committee on Nonlinear Systems and Control (2013-2015). He has served on the operating committees several conferences and will be the program chair of the 2018 American Control Conference. He currently serves on the editorial boards of several journals and book series, including Automatica, Systems & Control Letters, Science China Information Sciences, and Springer/Birkhauser book series Control Engineering. He is a Fellow of the IEEE, a Fellow of the IFAC, and a Fellow of AAAS, the American Association for the Advancement of Science.

Speech Title: A Low Gain Feedback Approach to Dealing with Actuator Saturation and Input Delays

A smaller control input is less prone to actuator magnitude saturation. A more slowly varying control input is less prone to actuator rate saturation. Similarly, a more slowly varying control input is less sensitive to the delays in the input. Low gain feedback results in small and slowly varying control input and thus is effective in dealing with actuator saturation and/or input delays. In this talk, we review some key properties of low gain feedback and show how it leads to semi-global stabilization of linear systems subject to actuator saturation and stabilization of linear systems in the presence of an arbitrarily large bounded input delay. These developments indicate an underlying connection between actuator saturation and input delays.