Speakers of 2024

Prof. Mouquan Shen, Nanjing Tech University, China

Profile: Mouquan Shen received a Ph.D. degree in Control Theory and Control Engineering from the College of Information Science and Engineering, Northeastern University, Shenyang, China, in 2011. Since 2012, he has been with the College of Electrical Engineering and Control of Science at Nanjing Tech University, Nanjing, China. Since 2018, he has been a full professor at Nanjing Tech University, China. From 2015 to 2021, he was a visiting scholar at Yeungnam University, the University of Hong Kong, Hong Kong, and the University of Adelaide, respectively. His research interests cover fuzzy systems, iterative learning control, adaptive dynamic programming, networked control systems, hybrid systems, and so on. He has published over 90 international journal papers and received over 1900 citations with an h-index of 24.

He has served as Editor-in-Chief for Advances in Fuzzy Sets and Systems and Associate Editor for ISA Transactions, Proc. IMechE Part I: Journal of Systems and Control Engineering, International Journal of Robotics and Control Systems. He is also an active reviewer for over 70 international journals, such as IEEE Transactions on Automatic Control, IEEE Transactions on Cybernetics, IEEE Transactions on Systems Man Cybernetics-Systems, and IEEE Transactions on Fuzzy Systems. 

Link: https://eecs.njtech.edu.cn/info/1146/4885.htm

Title: Data-driven event-triggered control for intelligent manufacture systems

Abstract: This talk focuses on data-driven event-triggered control for intelligent manufacture systems. Based on the modified index, two optimal data-driven control laws are provided by employing adaptive dynamic programming method and Q-learning algorithm, respectively. Two novel event-triggered mechanisms are constructed by utilizing instantaneous and averaged data as well as performance cost, respectively. Sufficient conditions are developed to ensure the ultimately uniform boundedness of the resultant systems. Finally, some examples are presented to verify the effectiveness of the proposed schemes.

Prof. Jiangping Hu, University of Electronic Science and Technology of China, China

Profile: Prof. Jiangping Hu received a B.S. degree in applied mathematics and a M.S. degree in computational mathematics from Lanzhou University, Lanzhou, China, in 2000 and 2004, respectively, and a Ph.D. degree in Modeling and Control of Complex Systems from the Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China, in 2007. He has held various positions with the Royal Institute of Technology, Stockholm, Sweden; the City University of Hong Kong, Hong Kong; Sophia University, Tokyo, Japan; and Western Sydney University, Sydney, NSW, Australia. He is currently a professor at the School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China. His current research interests include multi-agent control, social dynamics, and distributed optimization. He has published more than 150 peer-reviewed papers, 12 ESI papers, and received over 7300 citations with an h-index of 33. He has been ranked among the world’s top 2% of most-cited scientists by Stanford University since 2020. He is an associate editor of the Journal of Systems Science and Complexity, Kybernetika, Mathematics, and PLOS Complex Systems.

Title: Safe and Fast Tracking Control for Complex Nonlinear Systems

Abstract: The fast and safe tracking control of complex nonlinear systems has important theoretical research value because of its wide practical application background. This kind of tracking control problem should not only satisfy the complex state constraints, but also ensure the convergence time. Firstly, this talk introduces the predefined-time tracking control method for uncertain strict feedback nonlinear systems with state constraints. The original system is transformed into a new unconstrained system by nonlinear transformation method. Using the method of time base generator, a smooth time base generator function suitable for any order system is constructed, and a predefined-time tracking controller based on a time base generator is designed by using an adaptive neural network technology and backstepping method, which realizes the target tracking of uncertain nonlinear systems in any predefined time. Then, the predefined-time tracking control method of an uncertain nonlinear multi-agent system under complex state constraints is introduced. In order to reduce the computational complexity of controller design, a predefined-time filter based on a time base generator function is proposed. Using an adaptive control and fuzzy control technology to realize multi-agent safe and fast tracking.

Assoc. Prof. Sohrab Mirsaeidi (SMIEEE), Beijing Jiaotong University, China

Profile: Sohrab Mirsaeidi received his Ph.D. degree in Electrical Engineering from Universiti Teknologi Malaysia (UTM), Malaysia, in 2016. Subsequently, he furthered his postdoctoral fellowship at the Department of Electrical Engineering, Tsinghua University, China, from 2016 to 2019. Currently, he is an Associate Professor at the School of Electrical Engineering, Beijing Jiaotong University (BJTU), China. Sohrab Mirsaeidi has published 60+ papers and two books in the field of microgrids and large-scale power systems. He is a member of the National Technical Committee of Measuring Relays and Protection Equipment Standardization of China and has presided over and participated in several national research projects in China. He is an editorial board member for several international journals and a regular reviewer for IEEE Transactions journals. He has also served as Chair, Keynote/Invited Speaker, and Technical Committee Member in 60+ international conferences. His main research interests include the control and protection of large-scale hybrid AC/DC grids and microgrids, power system stability, and the application of power electronics in power systems. He is a senior member of IEEE and a member of IET, CIGRE, and the Chinese Society for Electrical Engineering (CSEE). Link:http://faculty.bjtu.edu.cn/9358/

Title: Vulnerability Assessment of Large-Scale Hybrid AC/DC Power Grids Against Commutation Failure Incidents Using Advanced Simulation-Based Strategies

Abstract:HVdc transmission technology has been extensively utilized around the world due to its numerous advantages such as increased flexibility in operation, expanded power transfer capability, and easier interconnection of energy sources. With the increasing deployment of dc transmission in the existing ac networks, the possibility of ac and dc circuits running parallel to each other and sharing the same right-of-way or even the same tower is increasing, and hence hybrid ac/dc power grids are rapidly developing. The ac and dc grids have their own characteristics; an ac grid tends to have a large inertia and well-understood responses to disturbances, while a dc grid generally has a low tolerance to fault and can respond very quickly. While the number of ac/dc interconnections gradually increases in the hybrid grids, the mutual influence between ac and dc systems becomes more pronounced, and substantially more complex dynamic and transient interactions may occur; for example, a single ac system fault may lead to simultaneous commutation failures in multiple converter stations. Therefore, one of the main challenges associated with the reliability enhancement of future hybrid ac/dc grids is to identify and analyze the newly emerging contingencies. In this talk, first, the challenges of commutation failure and cascading fault in large-scale hybrid ac/dc grids are discussed, and then the main merits and demerits of the existing approaches addressing these challenges are presented. Finally, an automatic data-sharing platform for connecting PSCAD/EMTDC and MATLAB will be introduced which can combine the main advantages of both software packages and facilitates vulnerability assessment of large-scale hybrid ac/dc power grids against commutation failure incidents.

Assoc. Prof. Mohd. Khair b. Hassan, University Putra Malaysia, Malaysia

Profile: Mohd Khair Hassan was born in Melaka, Malaysia, in November 1974. He received his BEng (Hons) degree in Electrical and Electronics from the University of Portsmouth, United Kingdom, in 1998 and his MEng degree in Electrical Engineering from the University of Technology Malaysia (UTM). He later completed his Ph.D. degree, specializing in automotive engineering, from the University Putra Malaysia (UPM) in 2010. Currently, he is the Deputy Dean of Research and Innovation at the Faculty of Engineering, University Putra Malaysia, and a registered professional engineer in the field of electronics under the Board of Engineers Malaysia (BEM). Additionally, he is a Malaysian Board of Technology (MBOT)-certified professional technologist. He is currently serving as vice president of the Malaysian Society for Automatic and Control Engineers (MACE), also known as IFAC-MACE Malaysia, and is an IEEE senior member. Control systems, battery systems, and AI applications are among his areas of interest. His research team focuses on RUL prediction, energy management, battery balancing, and battery modeling. In journals, he has authored over 78 publications and five book chapters. Currently mentoring 16 PhD and 5 MSc students, he has graduated 12 PhD and 15 MSc students. He also serves on the Engineering Accreditation Council (EAC) and Engineering Technology Accreditation Council (ETAC) panels that accredit electrical and electronic (EE) programs appointed by the Malaysian Board of Engineers. He also serves as an external examiner for PhD and MSc students from Malaysian and international universities. Additionally, he serves as an evaluator and expert panel member for a variety of grant applications. Link: CURRICULUM VITAE (upm.edu.my)

Speech Title: Circular Economy and Battery Ageing

Abstract: Batteries play a crucial role in various industries, from electronics to electric vehicles and renewable energy storage. However,  battery ageing, which refers to the gradual deterioration of a battery's capacity and performance over time, presents challenges  in terms of sustainability and resource management. Embracing a circular economy approach can offer solutions to mitigate the environmental impact of battery ageing while maximizing the value extracted from used batteries.

Updating...