MEAE 2026 | 机械工程与航空航天工程·Mechanical Engineering and Aerospace Engineering

Special Session 7

Distributed Multi-Agent Formation Control for UAVs

Distributed formation control is pivotal for scalable, robust, and efficient UAV swarms. Advances in communications and autonomy are shifting systems to decentralized architectures, where the synergy of control protocols and sensing enables autonomous navigation, formation keeping, and collaborative tasks, from search and rescue to monitoring and inspection.

The goal of this Special Issue is to collect papers (original research articles and review papers) to give insights into pioneering research and practical innovations in distributed multi-agent formation control for UAVs. We invite contributions addressing the latest control methodologies, theoretical breakthroughs, and real-world flight implementations.

This Special session will welcome manuscripts that link the following themes, including, but not limited to:

Robust adaptive control for UAVs under aerodynamic disturbances, time-varying delays, and switching topologies.
AI-enhanced UAV coordination: deep reinforcement learning and data-driven approaches for formation flight and trajectory tracking.
Safety-critical UAV navigation: distributed collision and obstacle avoidance in dynamic, constrained, or densely populated environments.
Resilient heterogeneous UAV systems: fault-tolerant formation control under actuator/sensor failures, and cooperative control of heterogeneous multi-agent systems

Submission Guideline:

Please submit your manuscript via Online Submission System: https://easychair.org/conferences/?conf=meae2026
Please choose "Special Session 7"

Organizers:

Zhen Jia, Northwestern Polytechnical University, China

Zhen Jia, Associate Professor and Master's Supervisor. Her primary research interests include condition monitoring and operation & maintenance of airborne equipment, fault-tolerant control of flight control systems, and intelligent detection of low-altitude targets. She has published 25 papers as first author or sole corresponding author in journals such as IEEE Transactions on Industrial Electronics, IEEE Transactions on Industrial Informatics, IEEE Transactions on Aerospace and Electronic Systems, and IEEE Transactions on Instrumentation and Measurement, including 2 ESI Highly Cited Papers. In total, she has authored over 50 SCI-indexed journal papers. She holds 6 authorized national invention patents and has received one Second Prize of the Shaanxi Provincial Science and Technology Progress Award. She serves as a Youth Committee Member of the Reliability Branch of the Chinese Society of Aeronautics and Astronautics. She has served as the principal investigator for a total of 11 research projects funded by national, and provincial agencies.

Bodi Ma, Chang’an University, China

Dr. Bodi Ma received the Ph.D. degree in Transportation Engineering from Northwestern Polytechnical University, Xi’an, China. He is currently a Lecturer with the School of Information Engineering, Chang’an University, Xi’an, China. His research interests mainly include intelligent control systems, unmanned aerial vehicle control, UAV tracking and formation control, reinforcement learning, multi-agent decision-making, and autonomous navigation in complex environments. He has been engaged in research on learning-based control methods for UAV systems, with particular emphasis on robust trajectory tracking, cooperative formation control, and intelligent decision-making under dynamic and uncertain conditions.