Tutorial and Workshops

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

Biography: 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

Biography: 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

Biography: 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.

11:30-12:00 Keynote C-3

Transferable Computational Intelligence Algorithm and Application

Biography: Cuie Yang, Ph.D., is currently a professor at the State Key Laboratory of Synthesize Automation for Process Industries of Northeastern University. She serves as a Associate Editor of IEEE TNNLS and as a reviewer for several authoritative domestic and international journals and conferences. She has engaged in the research of transfer learning, multi-task evolutionary optimization, and data-driven evolutionary optimization for many years. She has published more than 20 articles including 10 in top-tier journals, such as IEEE TEVC, IEEE TNNLS. Her academic results has achieved awards including the first prize of the Liaoning Province Natural Science Award (ranked 3rd), one of China’s Top 100 Most Influential Domestic Academic Papers, a nomination for the Excellent Doctoral Dissertation Award from the Chinese Association of Automation, the Liaoning Province Outstanding Master's Thesis Award, and the Leader F5000 China's Top-Quality Journal Top Paper Award.

14:15-14:45 Keynote J-2

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

Biography: 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

Biography: 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

Biography: 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

Biography: 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

Biography: 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

Biography: 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

Biography: 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

Biography: 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

Biography: 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

Biography: 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

Biography: 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

Biography: 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

Biography: 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

Biography: 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.