Xin Qi
University of Science and Technology Beijing, China

Biography: Xin QI, Professor, IEEE Senior Member, leader of the Academic Team on Control and Simulation of Electromechanical Systems, University of Science and Technology Beijing, University Distinguished Teacher.  He received the B.S. and Ph.D. degrees in electrical and mechanical engineering from the University of Science and Technology Beijing, China, in 2004 and 2011, respectively. He was a Research Assistant with the Electrical Machines and Drives Laboratory, University of Wuppertal, Wuppertal, Germany, in 2009, 2010, and 2012. He was a Visiting Scholar with the Electrical Machines and Drives Laboratory, University of Wuppertal, Wuppertal, Germany, in 2018/2019. His research interests include sensorless control of AC machines, online optimized pulse-width modulation techniques, and control strategies for inverters and AC machine drives.

Speech Title: Predictive Control Previous and Present

Abstract: "Predictive Control" is a very fashionable research topic at present. It first emerged in the 1970s. Jacques Richalet and Cutler, invented this method for application in the process control of the chemical industry, which is particularly suitable for control processes that change extremely slowly. However, in 1983, Professor Joachim Holtz, a German scholar, first proposed a predictive control method for AC motor drives, which require high dynamic performance and strong real-time capability. This method considers the inverter and the motor as a composite system, which has both "discrete states characteristic" and "continuous states characteristic" simultaneously. It predicts the electrical behavior of the motor under the action of all effective switching states of the inverter, and then, selects the optimal switching state for the future to drive the motor. This presentation will review the origin and development of the predictive control for AC motor drives, and also elaborate the latest research achievements.

 

Xia DONG
Xi'an Jiaotong University, China

Biography: Xia DONG, female, PhD in Engineering, doctoral supervisor and associate professor at the School of Mechanical Engineering in Xi'an Jiaotong University. She has hosted or participated in more than 10 projects sponsored by the National Natural Science Foundation of China (NSFC), the Ministry of Science and Technology (MOST), Major Special Projects for CNC Machine Tools, Shaanxi Provincial Key R&D Program, 863 sub-projects and enterprises. More than 60 scientific research papers including more than 50 SCI and EI indexed papers have been published. More than 10 authorized invention patents have been obtained in the fields of robotic technology and laser processing. The research achievement "Technology and Its Application of Autonomous Picking Robot Guided by Multi Information Fusion in Semi-structured Orchard Environment" won the second prize from Shaanxi Provincial Department of Education. She has obtained 2 collaborative education projects from the Ministry of Education and 3 teaching achievement awards in national and Shaanxi Province level. Her research fields mainly focus on machine vision, electromechanical system control, robot design and control and laser processing with high efficiency and accuracy.

Speech Title: Apple Picking Robot Design and Research Based on Thermal Images and Visible Light Images

Abstract: The need for intelligent and automated apple picking robots has become increasingly urgent with the increasing loss of rural labor and the aging population. The work of apple picking robot design and research based on thermal images and visible light images, supported by a key research and development project in Shanxi Province, will be presented in this speech. Robot structural design, apple target detection in complex open orchard environments, apple spatial positioning, and picking arm visual guidance technologies will be shared in the presentation.

 

Jiantao Shi

Nanjing Tech University, China

Biography: Jiantao Shi received the B.S. degree in electrical engineering and automation from Beijing Institute of Technology, Beijing, China, in 2011, and the Ph.D. degree in control science and engineering from Tsinghua University, Beijing, in 2016. From 2016 to 2021, he worked as a Research Fellow at Nanjing Research Institute of Electronic Technology, Nanjing, China. In Oct. 2021, he joined the College of Electrical Engineering and Control Science, Nanjing Tech University, where he has been a professor since 2021. His main research interests include distributed and cooperative control, fault diagnosis and fault-tolerant, health management. He is currently a Senior Member of IEEE, a member of the Editorial Boards of several journals.

Speech Title: Intelligent Health Assessment and Life Prediction of Phased Array Radar T/R Modules

Abstract： Phased array radar has become the mainstream of radar equipment in both military and civilian fields. The T/R module, as the core component of phased array radar, directly affects the performance of the entire radar system. Given the extreme and harsh conditions of temperature, pressure, vibration, and electromagnetic environment, T/R modules of phased array radar are highly susceptible to failures. Moreover, there are prominent issues such as unlabeled, imbalanced monitoring data and uncertainties in initial values. In recent years, our research group has conducted preliminary exploration and studies on the intelligent health assessment and life prediction of T/R modules in phased array radar. We have proposed a health assessment method based on multivariate deep forest and a life prediction method based on deep long short-term memory (LSTM) networks. These methods have been verified using real measured radar data.