In recent years, with the vigorous development of swarm intelligence in agriculture, industry, economy and other fields, the cooperative decision-making and control problem of large-scale intelligent, autonomous, and multi-functional swarm unmanned systems has received extensive attention. Among them, heterogeneous networked systems are more conducive to the implementation of cluster collaborative tasks due to their stronger task adaptability, higher system robustness, and higher resource utilization. This report mainly focuses on two kinds of decision-making and control problems, cooperative optimization and non-cooperative game control in heterogeneous networked systems, and constructs a decision-making and control integrated architecture. Based on output regulation theory, event-triggered control techniques and dynamic gain regulation methods, the decision-making and control scheme of cooperative optimization and non-cooperative game for heterogeneous networked systems is given. It achieves a fully closed loop, high robustness, and strong real-time control pattern. Finally, we discuss the prospects of integrating cooperative optimization and non-cooperative game problems with artificial intelligence techniques such as reinforcement learning and data-driven methods.

Chengxin Xian received the B.Eng. degree in Transportation Equipment and Control Engineering and Ph.D. degree in Control Science and Engineering from the School of Automation, Northwestern Polytechnical University, Xi’an, China in 2019 and 2024, respectively. Currently, he is a Post-doctoral Fellow in the Department of Applied Mathematics, The Hong Kong Polytechnic University. Prior to this, he was a Post-doctoral Fellow in the Department of Electrical Engineering, City University of Hong Kong. His research interests include cooperative control and optimization of clustered unmanned systems and their applications to multi-robot systems. Dr. Xian was the recipient of the Best Paper Awards of IFAC LSS in 2022, and IEEE ICUS in 2025.