Speakers

Prof. Li Guo, Hunan University, China

Biography: Prof. Li Guo  received  his PhD at Xian Jiaotong University, China in 1992.  He researched advanced machine tool with Prof. W.B.Rowe at Liverpool John Moores University, UK in 2003-2004, researched advanced materials grinding in airplane engine with Prof. Xun Chen at University of Nottingham UK in 2007 and researched advanced materials join in car body with Prof. S Jack Hu at University of Michigan, USA in 2014. Currently, he is a Doctoral/Master  Supervisor at Hunan University, National Science and Technology Evaluation Expert, Academic Backbone of Hunan University, Science and Technology Experts from 15 provinces including the Ministry of Education and Hunan Province, Evaluation Expert for Science and Technology Talent Awards of China Association for Science and Technology, National Graduate Education Quality Monitoring Expert, Vice Chairman of Changsha Mechanical Engineering Society, Manager of Hunan Yuelu Mountain Industrial Innovation Center, etc. He has published more than 80 papers on Journals. 

Speech Title:  Research on Intelligent Acoustic Emission Monitoring in the Grinding of Ceramics and Superalloys
Abstract: This study investigates the thermal acoustic emission monitoring of superalloys and alumina ceramics using the short-time Fourier transform acoustic emission signal processing technique. It explores the relationship between acoustic emission signals and grinding forces, grinding temperatures, and grinding damage in high-speed grinding of engineering ceramics. Additionally, intelligent acoustic emission monitoring of wheel wear during cylindrical grinding of superalloys is conducted. Artificial intelligence and deep learning neural networks are applied for the intelligent acoustic emission monitoring of surface roughness in ceramic grinding. This research addresses key challenges in the intelligent acoustic emission monitoring of difficult-to-machine materials, specifically engineering ceramics and superalloys, during grinding.

Prof. Shunli Wang, Inner Mongolia University of Technology, China

Academician of Russian Academy of Natural Sciences, IET Fellow

Biography: Shunli Wang, Professor, Doctoral Supervisor, Executive Vice President of Smart Energy Storage Institute, Academic Dean of Electric Power College at Inner Mongolia University of Technology, Academician of the Russian Academy of Natural Sciences, RSA Fellow, IET Fellow, IEEE Senior Member, Academic Leader of National Electrical Safety & Quality Testing Center, Tianfu Qingcheng Scientific and Technological Talent, High-level Overseas Talent, Tianfu A Talents, Academic and Technical Leader of China Science and Technology City, Top 2% Worldwide Scientist.

Speech Title:  Research and Application of Situation Awareness for Large scale Energy Storage Mechatronics in New Power Systems
Abstract:  To be updated

Prof. Zipeng Wang, Beijing University of Technology, China

Biography: Zi-Peng Wang (Senior Member, lEEE) received the Ph.D. degree in control theory and control engineering from Beihang University, Beijing, China in 2017. From July 2017 to August 2022, he was an Associate Professor with the School of Electrical Engineering, U niversity of Jinan, Jinan, Shandong, China. In September 2022, he joined the Faculty of Information Technology, Beijing University of Technology, Beijing. He was a ResearchAssistant with the City University of Hong Kong for six months in 2016. From December 2019 to January 2020, he was a Postdoctoral Research Associate with Texas A&M University at Qatar, Doha, Qatar. His current research interests include robust control and filtering, fuzzy modeling and control, secure control, discontinuous control systems, networked control systems, distributed parameter systems, and neural networks. Dr. Wang serves as an Associate Editor/Editorial Board Member for the IEEE Transactions on Automation Science and Engineering , the IEEE Systems, Man, and Cybemetics Magazine, the Applied Soft Computing and the Neural Prcessing Letters.

Speech Title:  Sampled-Data Fuzzy Control for Complex Dynamic Systems

Abstract: This speech focuses on complex dynamic systems based on three key scientific issues: T-S fuzzy modeling, stability and performance analysis, and sampled-data fuzzy controller design, with emphasis on introduction: 1. less conservatism sampled-data fuzzy control methods for nonlinear ODE/delayed ODE systems and applications; 2. sampled-data fuzzy control methods and applications for nonlinear PDE systems; 3. sampled-data fuzzy control methods and applications for nonlinear delayed PDE systems under multiple constraint conditions.