Affiliations: [a] Department of Statistics and Center for Mathematical Science, Wuhan University of Technology, Wuhan, China
| [b] Department of Mathematical and Center for Mathematical Science, Wuhan University of Technology, Wuhan, China
Correspondence:
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Corresponding author. Fei Gao, Department of Mathematical and Center for Mathematical Science, Wuhan University of Technology, Wuhan, 430070, China. E-mail: gaof@whut.edu.cn.
Abstract: Cooperative attack with unmanned aerial vehicles (UAVs) plays a critical role in modern military warfare. To achieve multi-swarm cooperative attack with obstacle avoidance of formation, this paper proposes a cooperative control strategy that integrates flight control and autonomous marshaling. Firstly, an improved dynamics model with virtual leader-following mode is constructed to achieve obstacle avoidance of the formation. And an improved interference fluid dynamic system (IIFDS) is applied to improve path selectivity during multi-swarm attack. Secondly, a two-layer attack framework based on distributed swarm coordinated trajectory tracking with heading angle constraints is designed to achieve autonomous clustering of the UAVs and target striking. Finally, the proposed improved dynamics model is compared with the particle swarm optimization (PSO) algorithm and artificial potential field (APF) method in terms of obstacle avoidance of formation to demonstrate its superiority, which can obtain better benefits. Furthermore, two simulations of multi-swarm cooperative attack are conducted to validate the effectiveness of the control strategy. The proposed method expands the application of UAVs attack with obstacle avoidance of formation and provides a valuable reference for modern military operations.
