Special Session 4

✦ Intelligent Control and Optimization for Complex Systems ✦

Advanced Methods for Complex System Modeling, Control and Optimization

Lead Organizer
Kaibo Shi
Kaibo Shi
Professor · Chengdu University
 
Kaibo Shi is a Professor at Chengdu University. From September 2014 to September 2015, he was a visiting scholar at the Department of Applied Mathematics, University of Waterloo, Waterloo, Ontario, Canada. He was a Research Assistant with the Department of Computer and Information Science, Faculty of Science and Technology, University of Macau, Taipa, from May 2016 to June 2016 and January 2017 to October 2017. He was also a Visiting Scholar with the Department of Electrical Engineering, Yeungnam University, Gyeongsan, South Korea, from December 2019 to January 2020. His current research interests include neural networks, cyber-physical systems, networked control systems, unmanned systems, power systems, and multi-agent systems. He is the author or coauthor of over 200 research articles. Dr. Shi was a recipient of the Highly Cited Researcher Award listed by Clarivate Analytics in 2021 and 2022, and the Highly Cited Chinese Researcher Award listed by Elsevier from 2021 to 2025. He serves as an editor of Fractal and Fractional and a guest editor of Sensors, Frontiers in Neurorobotics, and Advanced Engineering Sciences.
Lead Organizer
Song Zhu
Song Zhu
Professor · China University of Mining and Technology
 
Song Zhu was born in 1982. He received the B.S. degree in mathematics from Jiangsu Normal University, Xuzhou, China, in 2004, and the M.S. degree in probability and mathematical statistics and the Ph.D. degree in system engineering from Huazhong University of Science and Technology, Wuhan, China, in 2007 and 2010, respectively. He is currently a Professor with the School of Mathematics, China University of Mining and Technology, Xuzhou. He has published over 100 international journal papers. His current research interests include neural networks and stochastic control.
Lead Organizer
Xing-chen Shangguan
Xing-chen Shangguan
Professor · China University of Geosciences
 
Xing-chen Shangguan is a Professor and Doctoral Supervisor at China University of Geosciences , and a National-Level Young Talent. He has been selected for the Hubei Province "Chutian Scholar" Program, the Wuhan "Young Talent Program" (Outstanding Young Talent), and the China University of Geosciences "Young Top-notch Talent (Category A)" Program. He currently serves as a Director of the Hubei Association of Automation, a Committee Member of the Youth Work Committee and the Artificial Intelligence and Robotics Education Committee of the Chinese Association of Automation, and a Committee Member of the Embodied Intelligence Committee of the Chinese Society of Command and Control. He is a Member of both IEEE and the Chinese Association of Automation (CAA).
Co-Organizer
Fanghai Zhang
Fanghai Zhang
Associate Professor · Hefei University of Technology
 
Fanghai Zhang is an Associate Professor at Hefei University of Technology and a core member of the Huangshan's Scholars. He obtained his Ph.D in Control Science and Engineering from Huazhong University of Science and Technology in June 2018. He previously conducted postdoctoral research at Huazhong University of Science and Technology and Texas A&M University at Qatar. His main research interests include stability analysis and control of systems, theory and applications of attractors, associative memory, and brain-inspired intelligence. He previously served successively as an editorial board member for the journals Journal of Nonlinear Dynamics and Applications, Fractal and Fractional, and worked as a reviewer for journals including Neurocomputing, Neural Networks, Nonlinear Dynamics, IEEE Transactions on Neural Networks and Learning Systems, and IEEE Transactions on Cybernetics.
Co-Organizer
Yanyi Cao
Yanyi Cao
Associate Professor · Chengdu University
 
Yanyi Cao is an Associate Professor at Chengdu University. He received the B.S. degree in metallurgical engineering from Guangxi University, Nanning, China, in 2016, the M.E. degree in control engineering from Huazhong University of Science and Technology, Wuhan, China, in 2019, and the Ph.D. degree in computer science and technology from Sun Yat-sen University, Guangzhou, China, in 2024. From September 2019 to August 2020, he was a Research Assistant with the University of Electronic Science and Technology of China, Chengdu, China. His current research interests include neural networks, multi-agent systems. He serves as a Youth Editorial Board Member for Intelligence & Control, and a Guest Editor for IEEE Systems, Man, and Cybernetics Magazine.
Intelligent Control and Optimization for Complex Systems
面向复杂系统的智能控制与优化
Keywords: Complex Systems, Intelligent Control, Optimization, Networked Control Systems, Multi-Agent Systems

Introduction
Contemporary engineering systems are rapidly evolving toward large-scale, strongly coupled, highly dynamic, and deeply uncertain characteristics. Traditional control and optimization theories have become increasingly inadequate in addressing such complex systems. Meanwhile, the continuous iteration of neural network algorithms and the deepening of networked control theory have opened new avenues to overcome the challenges of modeling, controlling, and optimizing complex systems. Centered on "Intelligent Control and Optimization for Complex Systems," this special issue aims to foster interdisciplinary collaboration and promote the deep integration of advanced intelligent control methods, complex system optimization, smart grid applications, and networked control systems. It seeks to establish a complete research loop from fundamental theory to engineering implementation, effectively enhancing the intelligence level of complex systems.

Research Topics (include but are not limited to):
01

Advanced Intelligent Control Methods

先进的智能控制方法
  • Adaptive, robust, and event-triggered control for complex systems
  • AI-based control (reinforcement learning, neural networks, transfer learning)
  • Large language model-empowered control for complex systems
  • Swarm intelligence control for complex systems
02

Optimization of Complex Systems

复杂系统的优化
  • Large-scale, multi-objective, and stochastic optimization
  • Resilient optimization and risk-aware decision-making under uncertainty
  • LLM-empowered online evolutionary optimization and digital twin calibration
  • Swarm intelligence and distributed evolutionary optimization for complex systems
03

Smart Grid Control and Applications

智能电网控制与应用
  • AI-based grid load forecasting and optimal dispatch
  • Intelligent control of microgrids with distributed energy integration
  • Power system fault detection and power quality enhancement technologies
  • Data-driven grid security defense and resilient restoration
04

Networked Control Systems and Applications

网络化控制系统与应用
  • Networked control strategies in industrial internet environments
  • Distributed cooperative control of multi-agent systems
  • Secure control and defense of power systems under cyber attacks
  • State estimation and filtering for networked systems under communication constraints

ISCOA 2026 · Special Session