（一）
报告时间：3月26日（星期三）上午 09:00-09:50
报告地点：东湖国际会议中心
报 告 人：Tianyou Chai，Northeastern University, China
报告题目：Intelligent Decision and Control Integrating System Based on End-edge-cloud Collaboration
内容简介：To address the challenges in operation optimization decision and control of complex industrial system, this talk proposes the design method of intelligent optimal decision and control integrating system of complex industrial process. The design method of the system combines control and optimization with prediction, mechanism analysis with deep learning, and digital twin with reinforcement learning, realizing the self-adaption, self-learning, and self-optimization of the system. Based on the tight conjoining of and coordination between Industrial AI, Industrial Internet, Industrial Metauniverse technology and industrial automation and information technology, and by combining the end-edge-cloud collaboration technology of Industrial Internet and PLC control system, an intelligent decision and control integrating system based on end-edge-cloud collaboration is developed. The system has been successfully applied in the energy intensive equipment—fused magnesium furnace and achieved remarkable results in the reduction of carbon emission.
报告人简介：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. He has served as director of Department of Information Science of National Natural Science Foundation of China from 2010 to 2018. His current research interests include modeling, control, optimization and integrated automation and intelligence of complex industrial processes.
He has published 356 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 5 prestigious awards of National Natural Science, 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, and the 2017 Wook Hyun Kwon Education Award from Asian Control Association.
（二）
报告时间：3月26日（星期三）上午 10:10-11:00
报告地点：东湖国际会议中心
报 告 人：Tongwen Chen，University of Alberta, Canada
报告题目：New Research Problems in Industrial Alarm Monitoring Systems
内容简介：In operating industrial facilities, alarm systems are configured to notify operators about any abnormal situation. The industrial standards (EEMUA and ISA) suggest that on average an operator should not receive more than six alarms per hour. This is, however, rarely the case in practice as the number of alarms each operator receives is far more than the standard.
There exist strong industrial needs and economic benefits for better interpreting and managing alarms, and redesigning alarm systems to reduce false and nuisance alarms and increase the alarm accuracy. In this talk, we plan to summarize our recent work in this new area, targeting an intelligent and data-based approach, called “alarm analytics,” and presenting a new set of advanced tools for alarm visualization, performance evaluation and analysis, alarm rationalization design, alarm flood classification, and root cause diagnosis, thereby to help industrial processes to comply with the new standards. The tools have been tested with real industrial data and used by process engineers in Canada and elsewhere.
报告人简介：Tongwen Chen is currently a Professor and Tier 1 Canada Research Chair in Intelligent Monitoring and Control at the University of Alberta, Canada. He received the Beng degree in Automation and Instrumentation from Tsinghua University, and the MASc and PhD degrees in Electrical Engineering from the University of Toronto. His research interests include computer- and network-based control systems, event-triggered control, advanced alarm management and design, and their applications to the process industry.
Professor Chen is a Fellow of IEEE, the International Federation of Automatic Control, the Royal Society of Canada, the Canadian Academy of Engineering, as well as the Chinese Automation Association.
（三）
报告时间：3月27日（星期四）上午 08:30-09:20
报告地点：东湖国际会议中心
报 告 人：Mo-Yuen Chow，Shanghai Jiao Tong University, China
报告题目：Advancing Distributed Energy Resources (DERs) Control with Dynamic Energy
Management System (D-EMS)
内容简介：The increasing integration of distributed energy sources presents a significant number of challenges associated with managing a large-scale cyber-physical system within microgrids. To ensure reliable and efficient operation, there is a need to develop a scalable, dynamic and adaptable energy management framework in a multi-agent environment. Dynamic Energy Management (DEM) emerges as a promising solution, enabling real-time optimal operation of DERs in dynamic and time sensitive scenarios like disaster relief. Moreover, integrating Energy Storage Management (ESM) with DEM can further enhance the overall system reliability, and efficiency. A crucial advancement in realizing advanced energy management frameworks is the Digital Twins (DTs). This presentation introduces a dynamic energy management framework, developed by the Shanghai Jiao Tong University Advanced Diagnosis. Automation, and Control (ADAC) Lab. The proposed methodology enhances scalability, ensures adaptability, and accelerates the convergence of distributed algorithms to effectively mitigate with the dynamic and time-sensitive nature of the grid. It also explores the application of digital twin frameworks in dynamic microgrids and battery energy storage systems (BESS), to demonstrate and validate the proposed management framework through real-time monitoring and situational awareness.
报告人简介：Mo-Yuen Chow earned his degree in Electrical and Computer Engineering from the University of Wisconsin-Madison (B.S., 1982); and Cornell University (M. Eng., 1983; Ph.D., 1987). Dr. Chow has been a Professor at Shanghai Jiao Tong University since 2022. He is an Emeritus Professor in the Department of Electrical and Computer Engineering at North Carolina State University.
Dr. Chow’s recent research focuses on distributed control and management, smart micro-grids, batteries management, and mechatronics systems. Dr. Chow has established the Advanced Diagnosis, Automation, and Control Laboratory. He is an IEEE Fellow, the Co-Editor-in-Chief of IEEE Trans. on Industrial Informatics 2014-2018, Editor-in-Chief of IEEE Transactions on Industrial Electronics 2010-2012. He has received the IEEE Region-3 Joseph M. Biedenbach Outstanding Engineering Educator Award, the IEEE ENCS Outstanding Engineering Educator Award, the IEEE ENCS Service Award, the IEEE Industrial Electronics Society Anthony J Hornfeck Service Award, and the IEEE Industrial Electronics Society Dr.-Ing. Eugene Mittelmann Achievement Award. He is a Distinguished Lecturer of IEEE Industrial Electronics Society.
（四）
报告时间：3月27日（星期四）上午 09:20-10:10
报告地点：东湖国际会议中心
报 告 人：Jian Chu，SUPCON Technology Co., Ltd., China
报告题目：Frontier Technologies and Application in Process Industries
内容简介：As the scale of process industry goes bigger and bigger, the fundamental issues on safety/security, quality, cost, efficiency, green become top concerns for managers. Conventional control and optimization strategies are not good enough to solve those problems. On the other hand, the great progresses of ICT and AI create enormous opportunities for new technologies around control systems and industrial artificial intelligence in process industry. In this speech, we will give a picture about the future of a well-running process manufacturing plant, in which autonomous control and self-guided optimization are normally applied based on industrial artificial intelligence technologies. Some practical applications will well demonstrate.
报告人简介：Jian Chu graduated from Zhejiang University in 1982, and studied in Kyoto University from Oct. 1986 to Jan. 1989, obtained his PhD from Zhejiang University in 1989. Since 1989, he was with Zhejiang University as a post-doctoral, associate professor and full professor. He was awarded as a Changjiang scholar of Ministry of Education in 1999. He is founder & Editor-in-Chief of “IET Cyber-Systems & Robotics”.
Over the years, he was awarded two second-class prizes for the National Award for Science and Technology Progresses, and one second-class prize for the National Award for Technology Invention.
（五）
报告时间：3月28日（星期五）上午 08:30-09:20
报告地点：东湖国际会议中心
报 告 人：Milos Manic，Virginia Commonwealth University, USA
报告题目：IES & IEEE - Opportunities for Professional Growth and Leadership within the Largest Professional Organization in the World!
内容简介：Institute of Electrical and Electronics Engineers (IEEE), the world's largest professional organization with over 500,000 members around the world, gathers over 39 technical Societies and eight Technical Councils representing a wide range of IEEE technical interests. The Industrial Electronics Society, one of the top IEEE Societies, is one of the geographically and topically most diverse of IEEE societies. With over 11,000 members, some of the highest ranked journals in IEEE, 24 technical committees, over 60 conferences per year, IES offers a plethora of opportunities for young and established researchers, innovators, and industry members. This talk will provide insights into opportunities for professional growth and involvement in IES and IEEE as a whole. The talk is meant to be interactive - questions are welcomed!
报告人简介：Milos Manic is a Professor with the Computer Science Department and Director of VCU Cybersecurity Center at Virginia Commonwealth University. He completed over 50 research grants in AI/ML in cyber and energy and intelligent controls. He authored over 200 refereed articles, has given over 50 invited talks around the world, authored over 200 refereed articles in international journals, books, and conferences, holds several U.S. patents and has won 2018 R&D 100 Award for Autonomic Intelligent Cyber Sensor (AICS), one of top 100 science and technology worldwide innovations in 2018.
He is an inductee of US National Academy of Inventors (senior class of 2023, member class of 2019), and a Fellow of Commonwealth Cyber Initiative (specialty in AI & Cybersecurity).
He is an IEEE IES President (2024-2025), after serving in multiple IES officer positions, IEEE Fellow (for contributions to machine learning based cybersecurity in critical infrastructures), recipient of IEEE IES 2019 Anthony J. Hornfeck Service Award, 2012 J. David Irwin Early Career Award, 2017 IEM Best Paper Award, associate editor of IEEE Transactions on Industrial Informatics, IEEE Open Journal of Industrial Electronics Society, and IEEE IES Senior Life AdCom member. He served as AE of Trans. on Industrial Electronics, was a founding chair of IEEE IES Technical Committee on Resilience and Security in Industry, and was a General Chair of IEEE ICIT 2023, IEEE IECON 2018 (record breaking, over 1,100 participants), IEEE HIS 2019.
（六）
报告时间：3月28日（星期五）上午 09:20-10:10
报告地点：东湖国际会议中心
报 告 人：Xin Chen，China University of Geosciences, China
报告题目：Intelligent and Advanced Control Technologies for Deep Drilling
内容简介：Facing the growing energy demand and complex exploration environments, the deep Big data and artificial intelligence technologies provides strong support for the intelligence and advanced control of deep drilling. The intelligent decision-making systems built on machine learning and deep learning, along with multi-source data fusion and real-time monitoring systems based on big data, significantly enhance the perception capabilities of the deep drilling process, achieving precise and efficient drilling control. Combined with industrial internet and cloud platform technologies, the intelligent control systems support remote monitoring and collaborative optimization of multiple well sites, significantly improving efficiency and safety. In the future, the further integration of large AI models and advanced control technologies will drive deep drilling towards higher levels of intelligence, integration, and green development.
报告人简介：Xin Chen is Vice Dean and Professor of School of Automation, China University of Geosciences, Wuhan, China. He is IEEE Member and Hubei "Chutian Scholar" Distinguished Professor. Professor Xin Chen specializes in multi-agent systems, intelligent control, and machine learning. He earned his B.S. in Industrial Automation from Central South University, M.S. in Control Theory, and Ph.D. in Mechatronics from the University of Macau. He joined China University of Geosciences, Wuhan, China in 2014 as a professor and Ph.D. supervisor. Professor Chen has led multiple national and provincial projects, published 66 SCI/EI papers, and holds 48 patents. He actively participates in academic activities, having chaired and served on the committees of several conferences, and holds key roles in the Chinese Automation Society.
