海军航空大学,山东 烟台 264001
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收稿:2024-12-17,
网络首发:2025-12-25,
纸质出版:2026-02-28
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何云风, 卢建华, 史贤俊, 等. 复杂环境下基于同步DMPC的异构无人集群分组编队控制[J]. 兵工学报, 2026,47(2):241130.
HE Yunfeng, LU Jianhua, SHI Xianjun, et al. Grouping Formation Control for Heterogeneous Unmanned Swarm Based on Synchronous DMPC in Complex Environment[J]. Acta Armamentarii, 2026, 47(2): 241130.
何云风, 卢建华, 史贤俊, 等. 复杂环境下基于同步DMPC的异构无人集群分组编队控制[J]. 兵工学报, 2026,47(2):241130. DOI: 10.12382/bgxb.2024.1130.
HE Yunfeng, LU Jianhua, SHI Xianjun, et al. Grouping Formation Control for Heterogeneous Unmanned Swarm Based on Synchronous DMPC in Complex Environment[J]. Acta Armamentarii, 2026, 47(2): 241130. DOI: 10.12382/bgxb.2024.1130.
针对复杂环境下的异构无人集群分组编队问题,提出一种基于同步分布式模型预测控制(Distributed Model Predictive Control,DMPC)的编队控制算法。以异构集群为研究对象,建立分组分层控制框架;针对环境中同时存在的障碍、故障和干扰,给出对应的避障策略、故障隔离策略和干扰补偿方法,并结合控制框架将其整合为完整可行的编队控制方案。根据编队控制方案,基于同步DMPC理论、速度障碍法和干扰观测器理论,设计了集避障、容错、抗扰于一体的异构无人集群分组编队控制算法,并证明了算法下集群的稳定性和干扰估计误差的有界收敛性。仿真结果表明:所设计算法下的异构无人集群在复杂环境下兼具良好的避障、故障容错和抗干扰能力。
To address the problem of grouping formation control(GFC)for heterogeneous unmanned swarm in complex environments
a formation control algorithm based on synchronous distributed model predictive control(DMPC)is proposed. A grouping and layering control framework is established by taking heterogeneous swarm as the research object. An obstacle avoidance strategy
a fault isolation strategy and a disturbance compensation method are proposed for the simultaneous existence of obstacles
faults
and disturbances in the environment
and integrated into a complete and feasible formation control scheme based on the control framework. According to the formation control scheme
a heterogeneous unmanned swarm GFC algorithm
which integrates obstacle avoidance
fault tolerance
and disturbance resistance
is designed based on the synchronous DMPC theory
velocity obstacle(VO)method
and disturbance observer(DOB)theory. It is proved that the proposed algorithm ensures the stability of the swarm and the bounded convergence of disturbance estimation error. The simulated results show that the heterogeneous unmanned swarm under the proposed algorithm has good ability of obstacle avoidance
fault tolerance and disturbance resistance in complex environment.
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