Prof. Mohammed Chadli, University Paris-Saclay Evry, France

Speech Title: Intelligent Control Systems for Fault Detection and Diagnosis: Vehicles application

Abstract: Some results on methods of fault detection filter synthesis, and observer design, for a class of nonlinear systems will be proposed. Observer-based LMI synthesis methods for T-S systems subjected to unknown inputs are presented. Subsequently, multi-objective synthesis problem is discussed in FDI framework. When we are interested in these problems in finite frequency domains, these classic techniques (in infinite frequency domains) become quite restrictive. Indeed, the problem of multi-objective synthesis (H_ and H∞) in the finite frequency domain is addressed. In a fault diagnosis context, the generated residue must be as sensitive as possible to faults and as robust as possible against unknown perturbations by means of finite frequency performance indices.

Biography: Mohammed Chadli received his M.Sc (DEA) from the Engineering School INSA-Lyon (France, 1999) and from “Ecole Normale Sup.” (Mohammedia, Morocco), the Ph.D. thesis in Automatic Control from the University of Lorraine (UL), CRAN-Nancy in 2002. He was Lecturer and Assistant Professor at the “Institut National Polytechnique de Lorraine” (UL, 2000-2004). Since 2004, he was Associate Professor at the University of Picardie and is currently a Full Professor at the University Paris-Saclay Evry, IBISC Lab., France. He was a visiting professorship at the TUO-Ostrava (Czech Rep.), UiA (Norway), SMU-Shanghai (2014-2017), NUAA-Nanjing (2018-2024), and the University of Naples Federico II (Italy, 2019).
Dr. Chadli’s research interests include filtering and control problems (FDI, FTC) and applications to vehicle systems, intelligence systems, network systems, and cyber-physical systems. He is the author of books and book chapters (Wiley, Springer, Hermes), numerous articles published in international refereed journals and conference proceedings.
Dr. Chadli is a senior member of IEEE. He is on the editorial board (Editor, Associate Editor) of several international journals, including the IEEE Transactions on Fuzzy Systems, Automatica, the IET Control Theory and Applications, the Franklin Institute Journal, Asian Journal of Control … and was a Guest Editor for Special Issues in international journals and the Vice Dean of the Faculty of Sciences and Technologies (Univ Evry Paris-Saclay). He now serves as the Chair of the IEEE France Section Control Systems Society Chapte, and listed in “100 000 Leading Scientists in the World”.

Prof. Wen Kang, Beijing Institute of Technology, China

Speech Title: Stabilization of PDE systems and its application in Multi-agent systems

Abstract: Many important plants (e.g. flexible manipulators or chemical reactors) are governed by PDEs and are often described by models with a significant degree of uncertainty. Stabilization for infinite-dimensional PDE systems is a challenging problem. We aim to provide efficient methods for stabilization of PDEs and for PDE-based multi-agent deployment.

Biography: Prof. Wen Kang received the B.S. degree from Wuhan University, Wuhan, China, in 2009, and the Ph.D. degree from Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China, in 2014. From 2015 to 2017, she was a Postdoctoral Researcher with the School of Electrical Engineering, Tel Aviv University, Tel Aviv-Yafo, Israel. In 2022, she joined Beijing Institute of Technology as a Professor. Her research interests include distributed parameter systems, time-delay systems, multi-agent systems, intelligent control, and ADRC. Prof. Kang was supported by National-level young talent program, Beijng Nova program, Xiaomi Young Scholar program. She serves as Associate Editor for IMA Journal of Mathematical Control and Information, IFAC MICNON, Information and Control. She is a Senior Member of IEEE and CAA.

Assoc. Prof. Depeng Zeng, Harbin Engineering University, China

Speech Title: No mechanical load Measurement and testing methods for multi-unit permanent magnet synchronous machines

Abstract: So far, there are some problems in the measurement and test of the permanent magnet synchronous machine(PMSM) applied in the high-power systems and the special high-end equipment, such as complex test systems, high test cost, and testing difficult, etc. It restricts the research and application level of electric machine production severely.
Aimed at the multi unit PMSM, the indirect testing methods for important characteristics with no mechanical load are proposed by using the multi-winding. The parameters and characteristics of the machine in the load state can be reconstructed in the non-mechanical load state by the proper control strategies that make the physical fields in the two states are equivalent, it realizes the equivalent test with no mechanical load.
The inductance, resistance, temperature rise, mechanical characteristics, and torque fluctuation of the multi unit PMSM can be indirectly tested with the proposed methods without any load device. It may give a new way to test the important parameters and characteristics of the multi unit PMSM which the parameters and characteristics are difficult to obtain with the direct testing methods.

Biography: Depeng Zeng, Director of IEEE PES Motor Drive Special Committee, member of Youth Work Committee of China Shipbuilding Engineering Society, senior member of China Electrotechnical Society, system member of Aerospace Drive Youth Technical Committee, member of China Automation Society. He has presided over 5 vertical projects at the national and ministerial levels, 2 basic scientific research business fund projects of central universities, 6 horizontal projects, and participated in many national and ministerial-level projects as the main participant. Research directions include motor systems and intelligent drive control technology, special motor design and analysis, intelligent microgrid power supply and distribution system analysis, etc.

Assoc. Prof. Xianghua Wang, Beijing University of Posts and Telecommunications, China

Biography: Dr. Xianghua Wang is an IEEE Senior Member and an Associate Professor at the Beijing University of Posts and Telecommunications. She received her B.E. in Automation from Northwestern Polytechnical University in 2010 and her Ph.D. in Mechanical Systems and Control from Peking University in 2015. Between 2015 and 2023, she held several academic positions at Shandong University of Science and Technology, including Postdoctoral Researcher, Lecturer, and Associate Professor.

Her research expertise covers fault diagnosis, fault-tolerant control for unmanned systems (such as unmanned underwater and aerial vehicles), and secure control for cyber-physical systems. Dr. Wang has published 2 books, 3 book chapters, and over 80 research papers, with more than 40 high-quality journal publications as the first or corresponding author. Her academic excellence has been recognized through the Beijing Nova Program and the Xiaomi Young Scholar award. Furthermore, she leads three projects funded by the National Natural Science Foundation of China.

Assoc. Prof. Yuchen Jiang, Harbin Institute of Technology, China

Biography: Dr. Yuchen Jiang is an Associate Professor and Doctoral Supervisor with Harbin Institute of Technology. His research interests include data-driven fault diagnosis, process monitoring, and the safety and security of industrial cyber-physical systems. He is a Senior Member of IEEE, and a Member of the CAA Professional Committee on Fault Diagnosis and Safety of Technical Processes, and on Process Control. He has been ranked as a World’s Top 2% Researcher (Elsevier & Standford University) over the past five years (2021-2025). He served as an Associate Editor for top-tier journals such as IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, IEEE TRANSACTIONS ON CYBER-PHYSICAL SYSTEMS, and JOURNAL OF INDUSTRIAL INFORMATION INTEGRATION. Homepage: https://homepage.hit.edu.cn/jiangyuchen

Assoc. Prof. Jing Zhu, Nanjing University of Aeronautics and Astronautics, China

Biography: Jing Zhu received the B. E. degree in Communication Engineering from Nanjing University of Posts and Telecommunications, Nanjing, China, in 2010, and the Ph.D. degree in Electronic Engineering from City University of Hong Kong, Hong Kong, China, in 2015.

Dr. Zhu was a visiting scholar with the Department of Electrical and Computer Engineering, University of California, Riverside, US, from December 2013 to June 2014. She was also a post-doctoral fellow with the Faculty of Innovation Engineering, Macau University of Science and Technology, from 2021 to 2023, as the recipient of “2020 Macao Young Scholars” Scheme. Currently, she is the Associated Professor with the College of Automation Engineering, Nanjing University of Aeronautics and Astronautics.

She is in charge of many high-level research projects, including the National Natural Science Foundation of China, Special Funding for China Postdoctoral Researchers, General Funding for China Postdoctoral Researchers, and National Foreign Expert Program, etc. She has authored over 50 papers published in academic journals and conferences. Her research interests include blockchain technology, multi-agent systems, secure control and distributed artificial intelligence. Her current study focuses on multi-agent systems subjected to typical cyber-attacks and dynamic topology in complex environments.

Assoc. Prof. Chuan Luo, Sichuan University, China

Speech Title: Scalable Distributed Rough Hypercuboid Approach

Abstract: The popularity of granular computing, to a large extent, is due to the theory of rough sets. As a concrete theory of granular computing, rough set model enables us to tackle incomplete knowledge, manage the inconsistent information, and manipulate different levels of granularity. In that context, much attention has been paid and continues to be given to the rough sets in modeling and propagating uncertainty from both theoretical and applied points of view. The selection of prominent features for building more compact and efficient models is an important data preprocessing task in the field of data mining and machine learning. Rough set offers a powerful information granulation-oriented feature selection framework from data with imprecise, inconsistent and incomplete information. Noting that there is a growing consensus among the data science communities that the proliferation of data volume presents an immediate challenge pertaining to the scalability issue in recent years. As a practical pathway to pursue the challenge of explosive growth of data, parallelization of algorithms by exploiting high performance computing resources in a distributed computing environment have increasingly gained strengths in facilitating large-scale data analysis. In this tutorial, we focus on the scalability aspect of the rough sets-related research. We will introduce our recent attempts for improving the scalability of rough feature selection approach via the parallel and distributed optimization under the premise of ensuring accuracy.

Biography: Dr. Chuan Luo is currently an Associate Professor with the School of Artificial Intelligence, Sichuan University, Chengdu, China. He received the Ph.D. degree in Computer Science from Southwest Jiaotong University, Chengdu, China, in 2015. He was a Visiting Ph.D. Student with the University of Regina, Regina, SK, Canada, in 2014. In Feb. 2019, he was a Visiting Scholar with the Harvard University, Cambridge, MA, USA.
His current research interests include artificial intelligence, data mining, machine learning, and granular computing. He has published more than 100 research papers in international conferences and journals, such as the IEEE TKDE, IEEE TPDS, IEEE TNNLS, IEEE TFS, IEEE TMM, etc. He serves as editors of International Journal of Computational Intelligence Systems, Human-Centric Intelligent Systems, and CAAI Transactions on Intelligent Systems. He has been consecutively selected for Stanford University's List of the World's Top 2% Scientists (Annual Scientific Impact Ranking).

Assoc. Prof. Zicheng Wang, Northeast Forestry University, China

Speech Title: Optical Sensing in Robotic Hand Tactile Sensing Technology

Abstract: This report addresses a key issue in humanoid robotic fingertips: insufficient perception of tangential force by tactile sensors. To tackle this problem, we explore a novel sensing scheme based on a dual-period coupling of biomimetic cilia and assembled long-period fiber gratings. Drawing on the mechanical amplification mechanism of biological cilia, we employ magnetorheological elastomers to fabricate flexible cilia arrays, converting contact forces into changes in the refractive index of the medium driven by the photoelastic effect, thereby modulating the resonance spectrum of long-period gratings and establishing a quantitative sensing model that correlates the mechanical response of the cilia with optical signal drift. By utilizing an external magnetic field for non-contact adjustment of the cilia stiffness, we achieve, for the first time, real-time online tuning of sensor sensitivity and range. This research provides substantial technical support for the sensing and control of humanoid robotic hands.

Biography: Zicheng Wang, Associate Professor at the School of Control and Information Engineering, Northeast Forestry University, and Postdoctoral Fellow in Electrical Engineering at Harbin Institute of Technology, has long been engaged in the development of integrated optical devices and research in the fields of optical fiber communication sensing and system technology. He has achieved certain innovative results in areas such as highly integrated optical equipment, distributed long-distance optical fiber communication, and shipborne fiber-optic current measurement technology, with a multidisciplinary research foundation and experience spanning integrated optics, optical fiber communication, electronic science and instrumentation. He has led more than 10 projects, including the National Natural Science Foundation Youth Project, Heilongjiang Provincial Natural Science Foundation Youth Project, Aviation Science Foundation Project, Central University Fundamental Research Project, and military-industrial horizontal projects, with cumulative funds exceeding 10 million RMB. In the past three years, as first/corresponding author, he has published 21 SCI papers in authoritative journals such as OE, OLT, OL, and SJ, with a total of over 50 academic papers and 3 national key publications. He also serves as a young editorial board member for journals including Smart Sensors, Semiconductor Optoelectronics, and Journal of Naval Aeronautical and Astronautical University. He has been awarded the First Prize of the National Defense Science and Technology Progress Award and the Second Prize of the Heilongjiang Provincial Science and Technology Invention Award.

Dr. Sukarnur Che Abdullah, National Panasonic Malacca, Malaysia

Biography: Sukarnur Che Abdullah earned his PhD in Information Science from the Graduate School of Information Science, Nagoya University, Japan in 2012. The author’s major field of research is robotics, tactile sensors, airflow sensors, humanoid robots, vision sensors and advanced manufacturing systems engineering. Furthermore, he is currently working as a Senior Lecturer at Universiti Teknologi MARA, Malaysia, under the Mechanical Engineering Faculty since 2002. He had 2 years (2000-2002) of working experience as a Production Quality Engineer at National Panasonic Malacca, Malaysia.