Tutorial and Workshops

 

Workshop 1

Tuesday August 27th, 11:00-17:15, Room A101

 

SICE-TCCT Joint Workshop on Theory and Practice in Optimization, and Reinforcement Learning

 

Scientific Steering Committee:

Tielong Shen, Chair, Director of SICE

Yanlong Zhao, President of TCCT, Chinese Academy of Sciences, China

Jinliang Ding, Dean of School of AI, Northeastern University, China

Yuhu Wu, Dean of School of Control Science and Engineering, Dalian University of Technology, China

Jinwu Gao, Professor, Jilin University, China

Kang Song, Professor, Tianjin University, China

Kenji Terada, General Chair of SICE-FES 2024, Tokushima University, Japan

Kenji Ikeda, IPC Chair of SICE-FES 2024, Tokushima University, Japan

Yasuaki Oishi, General Chair of SICE-FES 2025, Nanzan University, Japan

Kiminao Kogiso, General Chair of SICE-FES 2026, The University of Electro-Communications, Japan

Kang-Zhi Liu, Chiba University, Japan

 

Secretariat:

Zhenhui Xu, Tokyo Institute of Technology, Japan

Fuguo Xu, Chiba University, Japan

 

11:00-12:00 Keynote Session I

 

11:00-11:30 Keynote C-1

Online Identification and Clustering of Mixed Linear Regression

Zhixin Liu, Chinese Academy of Sciences, Beijing, China

Zhixin Liu received the B.S. degree in mathematics from Shandong University in 2002, and the Ph.D. degree in control theory from Academy of Mathematics and Systems Science (AMSS), Chinese Academy of Sciences (CAS) in 2007. She is currently a professor of AMSS, CAS, and the director of Key Laboratory of Systems and Control, CAS. She had visiting positions with the KTH Royal Institute of Technology, Sweden, University of New South Wales, Australia, and University of Maryland, College Park, USA. She is a coauthor of the SIGEST Paper in SIREV in 2014, and the co-recipient of the Best Theoretical Paper Award at the 13rd World Congress on Intelligent Control and Automation (WCICA). She serves as the vice-director of the Technical Committee on Control Theory, Chinese Association of Automation. Her current research interests include multiagent systems, distributed control, and distributed estimation and filtering.

 

11:30-12:00 Keynote C-2

Intelligent Control of Vehicle and Powertrains Based on Multi-scale Uncertainty Observation and Learning

Kang Song, Tianjin University, Tianjin, China

Kang Song, Associate Professor at Tianjin University, Ph.D. Supervisor, Deputy Director of the Department of Energy and Power Engineering at Tianjin University. His main research interests include intelligent control of internal combustion engines and vehciles. The team has developed the self-learning intelligent disturbance control algorithm for internal combustion engines, and has been put into practical application in several leading domestic enterprises. Fifteen unmanned rollers developed by the team have been in practical application at hydroelectric dams for over two years. Guiding graduate students, the team has won a total of 21 awards in world intelligent driving challenges, intelligent connected vehicle competitions, including gold and silver medals. They were the first in domestic universities to complete all testing projects for open testing road licenses for autonomous driving buses and have entered the formal operational stage on roads. Their research results have been published in over 50 SCI/EI papers, with over 20 Chinese invention patent applications, 2 PCT patent applications, 2 US invention patents, and 3 provincial and ministerial-level awards of first prize or higher, and 1 second prize. Their work has been covered by authoritative media such as People's Daily, Science and Technology Daily, CCTV, and Tianjin TV.

 

13:15-15:15 Keynote Session II

 

13:15-13:45 Keynote J-1

Open Design Philosophy for Advanced Disaster Response Robots

Koichi Osuka, Osaka University, Osaka, Japan

He graduated from a master's course at the Graduate School of Engineering Science, Osaka University in 1984. Joined TOSHIBA in the same year and worked at the Research & Development Laboratory. Became an assistant at the Faculty of Engineering, Osaka Prefecture University in 1986.After working as a lecturer and assistant professor, he became an associate professor at the Graduate School of Informatics, Kyoto University in 1998, a professor at the Faculty of Engineering, Kobe University in 2003, and a professor in the Department of Mechanical Engineering, Graduate School of Engineering, Osaka University in 2009, where he remains to this day.

 

13:45-14:15 Keynote C-3

Boundary control of nonlinear flexible beams

Yuhu Wu, School of Control Science and Engineering, Dalian University of Technology, China

Yuhu Wu received the Ph.D. degree in mathematics from the Harbin Institute of Technology, Harbin, China, in January 2012. Since September 2012, he has been an Assistant Professor with the Harbin University of Science and Technology, Harbin. He held a post-doctoral research position at Sophia University, Tokyo, Japan, from April 2012 to September 2015. In October 2015, he joined the School of Control Science and Engineering, Dalian University of Technology, Dalian, China, where he is currently a full Professor. His research interests are related to optimization, and nonlinear control theory and applications of control to Boolean networks, automotive powertrain systems, and unmanned aerial vehicles.

 

14:15-14:45 Keynote J-2

Adaptive and Predictive Control, and Their Application to Engine Control and Energy Management Strategy

Ikuro Mizumoto, Kumamoto University, Kumamoto, Japan

Ikuro Mizumoto received the B.E. degree, the M.E. degree, and the Dr. Eng. degree, all in mechanical engineering from Kumamoto University, Kumamoto, Japan, in 1989, 1991 and 1996 respectively. Since 1991, he has been with Kumamoto University, where he is currently a Professor in the Robot, Control and Instrumentation Group in the Faculty of Advanced Science and Technology. In 2000, he held a visiting position at the University of Alberta for 7 months via a research fellowship funded by the Ministry of Education of Japan. He has published extensively in academic journals, conference proceedings, and several textbooks in control engineering. His co-authored book ‘Simple Adaptive Control’ (in Japanese) received a 2011 best publication award from the Society of Instrument and Control Engineers (SICE). Over the last decade, his research interests have been adaptive control system design, output feedback-based control for nonlinear systems, output predictive control system design, and their applications to practical systems including engine control.

 

14:45-15:15 Keynote J-3

Optimal Nonlinear Sampled-Data Control with a Stable Manifold and Numerical Techniques

 Yasuaki Oishi, Nanzan University, Japan

 

Yasuaki Oishi is a Professor within the Department of Mechanical Engineering and System Control, Nanzan University, Nagoya, Japan. His research interests include robust control, sampled-data control, and a mathematical programming approach. He is a General Co-Chair of SICE FES 2025 to be held in Chiang Mai, Thailand.

 

 

 

 

 

15:35-16:15 PhD Showcase (Poster + Flash Presentation)

 

Neural Inspired Hierarchical Reinforcement Learning Collaborative Framework for Robotics Motion Control

Pei Zhang, Northeastern University, China

Pei Zhang received his bachelor's degree from the School of Information Science and Engineering, Northeastern University, in 2021. He is a doctoral student in the Northeastern University School of Control Science and Engineering. His research interests include designing hierarchical reinforcement learning decision algorithms and researching robot control algorithms based on the neural system.

 

 

 

Path Tracking Control for Autonomous Driving with ADRC Parameter Optimization based on Deep Reinforcement Learning

Longqing Li,Tianjin University, China

Longqing Li is currently working toward a Ph.D. at the School of Mechanical Engineering, Tianjin University. He received his M.S. degree from Tianjin University, Tianjin, China, in 2021. His research interests include active disturbance rejection control, Autonomous vehicle control, and reinforcement learning.

 

 

 

Spatio-Temporal Directed Graph-Based Policy Optimization for Enhanced Negotiation in Autonomous Driving

Fan Guo, Tianjin University, China

Fan Guo received the B.S. degree in Energy and Power Engineering from the School of Energy and Power Engineering at Wuhan University of Technology, Wuhan, China, in 2020. He is currently pursuing a Ph.D. degree at the Center for Interdisciplinary Research on Autonomous Driving Technology at Tianjin University, Tianjin, China. His research interests lie primarily in the areas of decision-making and control of autonomous vehicles.

 

Integrated Power-Thermal Management of Connected Autonomous Hybrid Electric Refrigerated Trucks

Yunfeng Song, Yanshan University, China

Yunfeng Song received the B.S. degree in Mechanical Design & Manufacturing and Automation from Shandong University, Shandong, China, in 2018. He is currently pursuing the M.S. degree in Mechanical Engineering at Yanshan University, Hebei, China. His current research focuses on the energy-saving driving of refrigerated delivery trucks with hybrid power source under influence of complex external environmental factors and high-power controllable auxiliaries.

 

 

Driving Behavior Modeling and driving style Learning for Human-like Decision-Making

Yuepeng Wang, Yanshan University, China

Yuepeng Wang received the B.S. degree in mechanical engineering from Yangzhou University, Jiangsu, China, in 2021. He is currently working toward the M.S. degree in mechanical engineering with Yanshan University, Hebei. His research interests focus on advanced vehicles, including imitation learning for driving behavior modeling and decision-making, reinforcement learning for path planning, game theory for human-machine interactions.

 

 

 

Safety-Critical Control of FIWMD-EV Trajectory Tracking via Adaptive CVaR-based Control Barrier Function

Zongxuan Li, Tongji University, China

Zongxuan Li received the B.S. degree from Jilin University, Changchun, China, in 2023. He is currently working toward the M.S. degree with the Shanghai Research Institute for Intelligent Autonomous Systems, Tongji University, Shanghai, China. His main research interests include learning model predictive control and stochastic system safety filter control.

 

 

 

 

 

Fields Based Trajectory Planning and Inverse Model Predictive Control of Autonomous Vehicle

Chengye Wu, Yanshan University, China

Chengye Wu received the B.S. degree in vehicle engineering from Yanshan University, Qinhuangdao, China, in 2022. He is currently working toward the M.S. degree in mechanical engineering with Yanshan University, Qinhuangdao. His research interests and concerns are autonomous vehicle trajectory planning under multi risk factors coupling and driver decision-making style modeling, and advanced autonomous vehicle control algorithm.

 

Modeling Method of Human-like Driving Behavior Based on Environmental Situation Awareness

Jizhe Wang, Yanshan University, China

Jizhe Wang received the B.S. degree in mechanical engineering from Jiangsu University of Science and Technology, Jiangsu, China, in 2019, He is currently pursuing the Ph.D. degree in mechanical engineering at Yanshan University, Hebei, China. His current research focuses on the integrated framework of human-like driving behavior for autonomous vehicles, including driving risk assessment, human–machine shared driving and driving style learning and adaptive mechanisms.

 

 

 

16:15-17:15 Oral Session

 

16:15-16:30 J-4

Application of First-order Methods to Optimal Control Problem

Mitsuru Toyoda, Tokyo Metropolitan University, Japan

Mitsuru Toyoda received his Ph.D. degree in Mechanical Engineering from Sophia University in March 2018. Since April 2018, he has held a project assistant professor position at the Institute of Statistical Mathematics.  In April 2019, he joined Department of Mechanical Systems Engineering, Tokyo Metropolitan University, where he is currently an assistant professor.

 

 

 

 

 

16:30-16:45 C-4

Manifold-aware Collaborative Modeling Methods for Complex Industrial Process Monitoring

Xue Xu, Tiangong University, China

Xue Xu, received the Ph.D. degree in control theory and control engineering from the State Key Laboratory of Synthetical Automation for Process Industry, Northeastern University, Shenyang, China, in 2021. She is currently a Lecturer with Tiangong University, Tianjin, China. Her current research interests include modeling, process monitoring, and fault diagnosis for the complex industrial processes. She presided over a National Natural Science Foundation project. She has published more than 10 papers as the first/corresponding author in well-known journals in the field of process modeling and control, such as IEEE Transactions and IFAC Journal.

 

 

16:45-17:00 J-5

Covariance Analysis of an Estimated Markov Parameters in a Subspace Identification Method

Kenji Ikeda, Tokushima University Japan

Kenji Ikeda is an Associate Professor at Tokushima University, Tokushima, Japan.

His research interests includes system identification, optimization, and control engineering. He is a Program Chair of SICE FES 2024.

 

 

 

 

 

 

17:00-17:15 C-5

Safe Decision Making for Autonomous Vehicles: A Mixed Curriculum Reinforcement Learning Approach and A Novel Safety Switching Mechanism

Hongqing Chu, Tongji University, Shanghai, China

Hongqing CHU is an associate professor and doctoral supervisor at the School of Automotive Studies, Tongji University. He was selected for the Pujiang Talent Program in Shanghai in 2021. He has postdoctoral experience at Sophia University in Japan from 2019 to 2020. His research interests are vehicle control and intelligence, and he has presided over a number of scientific research projects such as the National Natural Science Foundation of China (NSFC), etc. He has published more than 30 high-level academic papers as the first/corresponding author, and he has won the only gold medal in the IEEE-CDC2023 Challenge for Automated Driving Control Algorithms, the only gold medal in the CAA-CVCI2022 Challenge for Energy Saving Algorithms for Electric Vehicles, the outstanding conference paper award of the society of automotive engineering, and the outstanding doctoral dissertation of Jilin Province.