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Journal of computing and information technology, Vol. 31 No. 4, 2023.

Original scientific paper

Distributed Computing Optimization in Unmanned Aerial Vehicle Swarm Cooperative Networks

Wangchun Luo ; Electric Power Research Institute of the Ultra High Voltage Transmission Company of China Southern Power Grid Co., Ltd., Guangdong, China
Xinghua Zhang ; Electric Power Research Institute of the Ultra High Voltage Transmission Company of China Southern Power Grid Co., Ltd., Guangdong, China
Fu Zhang ; Electric Power Research Institute of the Ultra High Voltage Transmission Company of China Southern Power Grid Co., Ltd., Guangdong, China
Zhibin Shi ; Electric Power Research Institute of the Ultra High Voltage Transmission Company of China Southern Power Grid Co., Ltd., Guangdong, China
Hongyi Liu ; Electric Power Research Institute of the Ultra High Voltage Transmission Company of China Southern Power Grid Co., Ltd., Guangdong, China

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Abstract

The Unmanned Aerial Vehicle (UAV) swarm cooperative networks across diverse domains present significant challenges in management and control to maximize collaborative efficiency, particularly in applications for large-scale and dynamic environments where real-time coordination is essential. This challenge has led to the development of a UAV swarm cooperative network flow prediction model, facilitating the strategic anticipation of network dynamics. A novel algorithm for distributed, finite-time cooperative control is introduced, grounded in this model. This algorithm optimizes the operational efficiency and control precision of UAV systems, while simultaneously augmenting the collaborative efficiency and stability of the UAV swarms. It marks a significant advancement in distributed computing strategies, offering a viable solution for the real-time coordination challenges in extensive UAV swarm cooperative networks. The proposed approach leverages multi-agent technology, integrating spatial-temporal constraints, location limitations, and path selection in cooperative behavior for dynamic and effective network management. This study not only enhances the understanding of UAV swarm dynamics but also contributes to the practical application of UAV swarms in areas requiring precise coordination and robust network stability.

Keywords

UAV swarm; cooperative network; flow prediction model; distributed control; multi-agent technology; system stability

Hrčak ID:

317640

URI

https://hrcak.srce.hr/317640

Publication date:

28.5.2024.

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