Ming-Zhe Dai is currently a lecturer in the School of Automation, Central South University, China. He received the Ph. D. degree in Control Science and Engineering from the School of Astronautics, Harbin Institute of Technology, China, in 2019. His current research interests are in the areas of Group intelligence and distributed cooperative control, Spacecraft attitude and orbit dynamics and its intelligent control, and UAV target detection, tracking and coordinated control. He has authored and co-authored more than 30 scientific papers published in peer-reviewed journals, receiving more than 200 citations in the past five years. In particular, his first-authored and corresponding-authored papers have appeared in several high-impact journals, including IEEE Trans. Syst., Man, Cybern., IEEE Trans. Cybern., IEEE Trans. Aerosp. Electron. Syst., and Int. J. Robust Nonlinear Control. He has been invited as peer reviewers for 10+ journals, including IEEE Trans. Autom. Control, IEEE Trans. Cybern., IEEE Trans. Syst., Man, Cybern., and IEEE Trans. Ind. Electron. He has presided over and participated in many scientific research projects, including the National Natural Science Foundation of China (NSFC) and China Aerospace Science and Technology Corporation (CASC) commissioned project.
In the past five years, Ming-Zhe Dai’s academic research mainly focuses on distributed multi-agent coordinated control, sampled-data control, spacecraft control and prescribed performance control, which are summarized as follows:
1. This scholar studied consensus and formation problems for multi-agent systems. The proposed prescribed performance control methods are suitable for multiple Euler-Lagrange systems and QUAD nonlinear multi-agent systems. These methods improve the state synchronization and tracking accuracies and improve robustness against external disturbances. The designed policies can be used for coordinated control of multi-UAVs and multi-manipulators and synchronization control of coupled chaotic circuits.
2. This scholar proposed distributed edge event- and self-triggered control policies for multi-agent networks. These intermittent Lebesgue sampling strategies schedule sensors, embedded computers, and communication devices on mobile robots to achieve information interaction with low resource consumption. These studies have the potential to be employed in the digital application of multiple-robot coordinated control.
3. This scholar designed event-triggered control policies for spacecraft attitude control. The investigated algorithms do not only save communication resources to deal with scenarios where internal communication between different modules is limited, but also can reduce the influences of external disturbances, inertia uncertainties, and actuator failure to improve state convergence accuracies. These theories can be employed in the digital control of plug-and-play modular spacecraft.
l 2020 Spring— Modern Control Theory for undergraduate students, 32 class hours
l 2022 Spring— Machine Learning for master students, 32 class hours
 Performance Research of Distributed Edge Event-Triggered Sampling, National Natural Science Foundation of China (NSFC)-Youth Fund Project, Project leader, 2023.01-2025.12.
Project Description: A study on the control performance of multi-agent systems based on edge-state measurement. In response to the current situation that the existing research on cooperative control of multi-agent systems is less considered from the perspective of system performance, we take edge state measurement sampling as the research object and study the performance level of distributed sampling control system by considering sensor sampling rate, computer algorithm complexity, communication network data transmission rate, actuator update rate and system state convergence characteristics, etc., and investigate the integral-type event-triggered mechanism, performance adjustable event-triggered mechanism, and prescribed performance control methods. This research explores the methods for designing, analyzing, and evaluating the performance of multi-agent systems, and its ability to provide theoretical reserves for practical engineering scenarios such as UAV clustering, multi-spacecraft collaboration, and spacecraft digital manufacturing design.
 Research on Gesture Control Technology for Assembly Return and Vertica Landing, China Aerospace Science and Technology Corporation (CASC) commissioned project, Project leader, 2019.11-2020.06.
Project Description: This project researches the return and vertical landing attitude control technology of the combined body mode such as rocket. It has designed and completed the key technologies such as rocket return and vertical landing attitude control technology scheme, rocket autonomous return and vertical landing high-precision attitude control technology, and rocket return and vertical landing heterogeneous actuator compliance control technology. The attitude control scheme and algorithm suitable for engineering applications are developed and validated and simulated. The designed attitude control scheme can determine the thrust magnitude, propellant consumption, and overall configuration requirements of the main engine, grid wing, and RCS for different stages of rocket return, and provide a theoretical basis for overall scheme design optimization.
IEEE Transactions on Automatic Control
IEEE Transactions on Aerospace and Electronic Systems
IEEE Transactions on Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics: Systems
IEEE Transactions on Control of Network Systems
IEEE Transactions on Industrial Informatics
IEEE Transactions on Industrial Electronics
IEEE Transactions on Circuits and Systems I: Regular Papers
IEEE Transactions on Circuits and Systems II: Express Briefs
Circuits, Systems & Signal Processing
Aircraft Engineering and Aerospace Technology