Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/115172
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Title: Distributed model predictive formation control for UAVs and cooperative capability evaluation of swarm
Authors: Yang, M
Guan, X 
Shi, M
Li, B
Wei, C
Yiu, KFC 
Issue Date: May-2025
Source: Drones, May 2025, v. 9, no. 5, 366
Abstract: This paper utilizes the distributed model predictive control (DMPC) method to investigate the formation control problem of unmanned aerial vehicles (UAVs) in the obstacle environment and establishes cooperative capability evaluation metrics of the swarm. Based on the DMPC approach, the formation cost function is constructed to adjust the relative positions and velocities of UAVs, ensuring the desired formation. Additionally, to address the obstacle avoidance problem in the formation, the obstacle avoidance function is designed to provide safe formation control in the obstacle environment. To evaluate the cooperative capability of UAVs, we design evaluation metrics from multiple dimensions to reflect the swarm’s cooperative capability. Finally, the simulation results show the effectiveness of the formation control method with obstacle avoidance and the applicability of the swarm’s cooperative capability evaluation metrics.
Keywords: Cooperative capability evaluation
Distributed model predictive control (DMPC)
Formation control
Unmanned aerial vehicles (UAVs)
Publisher: MDPI AG
Journal: Drones 
EISSN: 2504-446X
DOI: 10.3390/drones9050366
Rights: Copyright: © 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
The following publication Yang, M., Guan, X., Shi, M., Li, B., Wei, C., & Yiu, K.-F. C. (2025). Distributed Model Predictive Formation Control for UAVs and Cooperative Capability Evaluation of Swarm. Drones, 9(5), 366 is available at https://doi.org/10.3390/drones9050366.
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