Assoc. Prof. U Kei Cheang

Southern University of Science and Technology, China

Biography: Dr. U Kei Cheang is presently an associate professor in the Department of Mechanical and Energy Engineering at Southern University of Science and Technology (SUSTech). In 2015, he completed his Ph.D. degree in Mechanical Engineering at Drexel University, where he held the NSF GRFP, NSF IGERT, and NSF EAPSI Fellowships. Dr. Cheang joined SUSTech in 2017 and has been leading a team as an independent PI to develop micro- and nanorobots. His work on robotic microswimmers received the UNESCO Netexplo Top 10 Award in 2016. Dr. Cheang was awarded the MOST High-End Foreign Expert Award in 2019 and the Shenzhen Excellent Young Scholars Award in 2022.

Speech Title: Fabrication, Functionalization, and Control of Magnetically Actuated Achiral Microswimmers

Abstract: Recent developments in the field demonstrated the potential to use artificial robotic microswimmers to significantly improve various types of biomedical applications by enabling precision control at scales that are inaccessible using traditional surgery tools. For robotic microswimmers to be used in practical applications, they must be mass-manufactured at low cost using conventional technologies, functionalized for biomedical applications, remotely actuated using a magnetic field, and controllable in complex environments. To this end, researchers studied many different types of microrobots/swimmers to meet these criteria. Here, we introduce the magnetically-actuated achiral microswimmers, which require neither chirality nor flexibility to generate propulsion. Achiral microswimmers can be mass-manufactured using conventional photolithography, which is essential for practical applications. When controlled via a rotating magnetic field, the microswimmers can swim in bulk fluid, roll on surfaces, and navigate through microchannels with complex and narrow pathways, demonstrating their potential for targeted therapy. Characterization of their motion showed that non-Newtonian fluids did not hinder their swimming, indicating that achiral microswimmers can potentially adapt to different biofluids. The microswimmers were experimentally verified to be biocompatible and functionalized for various applications, including drug delivery, stem cell delivery, and biosensing. In this talk, we will present recent research on the fabrication, functionalization, and control of achiral microswimmers as well as discuss their potential as a microrobotic platform for biomedical applications.

 

Assoc. Prof. Tao Huang

Chongqing University, China

Biography: Tao Huang the Ph.D degree in mechanical engineering from Tsinghua University, Beijing, China, in 2017. He is currently an Associate Professor the College of Mechanical and Vehicle Engineering, Assistant to the Director of the State Key Laboratory of Mechanical Transmissions for Advanced Equipment, and the principal investigator of National Institute of Engineering Excellence Electrical Machinery and control Laboratory, Chongqing University, Chongqing, China. His research interests force on the dynamics and precision/ultra-precision motion control of complex electromechanical systems, such as integrated circuit manufacturing equipment, CNC machine tools and robots, etc. In the past five years, he has led projects such as National Natural Science Foundation, 173 Project, National Key R&D Program sub-projects, and published more than 20 papers in top journals in the field such as IEEE TIE, IEEE TII, IEEE/ASME TMECH, and MSSP.

Speech Title: Integrating Model-driven and Data-driven Friction Compensation for Precision Transmission Mechanism

Abstract: Precision transmission mechanism (PTM)’s positioning and tracking performances are strongly affected by nonlinear friction, which causes quadrant glitch. The mechanism of friction is very complex and difficult to model accurately. Therefore, in this paper, the data-driven method is integrated with the traditional model-driven friction compensation to further compensate the model error by hard-to-model and unmodeled dynamics. Specifically, this paper proposes a model-and-data-driven three-degree-of-freedom (3-DOF) control strategy integrating a feedforward controller, a feedback controller and a modified disturbance observer (DOB). The effectiveness of control strategy is verified by experiment and the results show that excellent friction compensation effectiveness and enhanced quadrant glitch rejection ability, improving the positioning and tracking accuracy in PTM.

A/Professor Farhad Shahnia

 Murdoch University, Australia

Biography: A/Professor Farhad Shahnia received his PhD in Electrical Engineering from Queensland University of Technology (QUT), Brisbane, in 2012. He is currently an A/Professor at Murdoch University. Before that, he was a Lecturer at Curtin University (2012-15), a research scholar at QUT (2008-11), and an R&D engineer at the Eastern Azarbayjan Electric Power Distribution Company, Iran (2005-08). He is currently a Fellow member of Engineers Australia, Senior Member of IEEE, and member of the Australasian Association for Engineering Education.
Farhad’s research falls under Distribution networks, Microgrid and Smart grid concepts. He has authored one book and 11 book chapters and 100+ peer-reviewed scholarly articles in international conferences and journals, as well as being an editor of 6 books.
Farhad has won 5 Best Paper Awards in various conferences and has also received the IET Premium Award for the Best Paper published in the IET Generation, Transmission & Distribution journal in 2015. One of his articles was listed under the top-25 most cited articles in the Electric Power System Research Journal in 2015 while one of his 2015 journal articles has been listed under the top-5 most read articles of the Australian Journal of Electrical and Electronics Engineering. He was the recipient of the Postgraduate Research Supervisor Award from Curtin University in 2015 and the Australia-China Young Scientist Exchange Award from the Australian Academy of Technology and Engineering in 2016.
Farhad is currently a Subject Editor, Deputy Subject Editor, and Associate Editor of several journals including IEEE Access, IET Generation, Transmission & Distribution, IET Renewable Power Generation, IET Smart Grid, IET Energy Conversion and Economics, and International Transaction on Electrical Energy Systems and has served 35+ conferences in various roles such as General, Technical, Program, Publication, Publicity, Award, Sponsorship, and Special Session Chairs.
Farhad has led the IEEE Western Australia Section as the 2020-2021 Chair, and was the 2019 Founding Chair of the IEEE Western Australia Industrial Electronics Society (IES) Chapter. He is currently the 2021-2022 Secretary of the IES’s Technical Committees on Smart Grids.

Speech Title: Role of Microgrids and Virtual Power Plants in Decarbonization

Abstract: Electricity systems around the world are experiencing a radical transition as the consequence of replacing fossil fuels, used for electricity production, by sustainable and cleaner energies. The growing penetration of renewable energies requires smarter techniques capable of handling the uncertainties of these intermittent sources. Along with this change, traditionally centralised power systems are also converting into distributed self-sufficient systems, often referred to as microgrids, that can operate independently. Virtual power plants are frameworks under which microgrids can be deployed within communities and enable energy transaction amongst retailers, customers and private investors. This talk will focus on the role of microgrids and virtual power plants in decarbonisation of the energy sector.

 

 

Assoc. Prof. Xiaoyang Kang

Fudan University, China

Biography: Xiaoyang Kang received his Ph.D. degree in electronic science and technology from the Shanghai Jiao Tong University, China, in 2016 and completed postdoctoral research at Ecole Polytéchnique Fédérale de Lausanne (EPFL). He joined Fudan University in 2018. Since January 2023, he has been the tenure-track associate professor in Institute of AI and Robotics, Academy for Engineering and Technology, Fudan University. He is the Deputy Secretary General of the Special Committee of Human Machine Integration Intelligence of the Chinese Association for Artificial Intelligence (CAAI). His research interests focus on the neural electronics, biomedical micro electronic devices and systems, neural engineering and brain computer interface, which can be applied to implantable / wearable rigid, flexible and soft neural interface devices, neural prosthesis, neural rehabilitation and other fields. He has led many projects with funding of more than 5M including the National Natural Science Foundation of China, the National Key R&D Program of China. He has published more than 70 journal and conference papers, including Neuron, Biosensors and Bioelectronics, IEEE Transactions on Neural Systems and Rehabilitation Engineering, Biomedical Signal Processing and Control.

Speech Title: Brain-computer Interface Controlled Hybrid Exoskeleton and Unmanned System

Abstract: The brain-computer interface (BCI) system converts EEG signals into computer-identifiable instructions directly to transmit information or realize the control of external devices, which is a brand-new way of human–computer interaction. The brain signals that represent the control intention of users can be decoded both in the normal and VR environment. The signal acquisition and processing module converts brain signals into specific control instructions and sends them to the controlled object through the VR system. At the same time, the target returns its behavior to the control side. The control commands and the target status interact between the VR system and the controlled target. In this talk, we will present recent research on the brain-computer interface and the bioelectronic controlled hybrid exoskeleton and unmanned system.

 

Assoc. Prof. Yongli Zhu

Sun-Yat Sen University, China

Biography: Yongli Zhu is presently an Associate Professor at the School of System Science and Engineering, Sun-Yat Sen University, Guangzhou, with a study focus on supporting the reliable and resilient operation of modern power grid. He received the B.S. degree from the Huazhong University of Science and Technology in 2009 and the Ph.D. degree from The University of Tennessee, Knoxville. His research interests include power grid reliability, power grid stability, and the applications of artificial intelligence to power grid operations. His previous working experience includes researcher and engineer roles, respectively, in TAMU, ISU, Amazon, and China State Grid Corporation.

Speech Title: Advances in the Development of Open-Sourced Tools for Power Grid Reliability Evaluation

Abstract: In this talk, Dr. Zhu will present his recent work on power grid reliability assessment (RA), a.k.a. resource adequacy analysis. The main goal of RA is to measure whether the power plant generation can satisfy the load demand to meet the capacity and energy needs in a particular period. Reliability assessment is critical to the secure operation of the modern power grid and our society. Probabilistic approaches have been widely utilized in RA, e.g., the Monte Carlo Simulation. With the expansion of the power grid, the penetration of renewable energy, and the recent impact of certain extreme weather events (e.g., the unexpected long-term iced rain during this year's spring festival in certain Chinese provinces), there is a need to revisit how fast the RA tool can perform and how easy to learn it for students and engineers. Existing RA tools include commercial tools and open-sourced tools. The former are usually too expensive to be affordable for educators and students; the latter are usually free, but most previous open-sourced RA tools run slowly and offer merely simple functionalities. Besides, lacking a user-friendly GUI has hindered university students' and junior engineers' learning pace and interest. In this talk, Dr. Zhu will introduce his recent year's developing work (previously supported by the Bill Gates Foundation in the U.S. and cooperated with other scholars) on two open-sourced tools for power grid reliability assessment: NARP (Fortran) and NARP (Python). This work, initiated in early 2021, aims to modernize an industry-grade RA tool for free use and fork by educators, researchers, and companies. Those open-sourced tools address several challenges related to reliability assessment in the real power industry. During the talk, case Studies of two example power grids were used to demonstrate the usage and capability of the developed tools, with an explanation of the results by tables and plots. The case study can provide the audience with a clearer understanding of the current capabilities of the industry-grade RA tool. The talk will conclude with a vision of leveraging certain of the latest machine learning and artificial intelligence approaches for further speed improvement of the RA task and discussing how to incorporate AI pipelines into NARP tools.