面向空地中继网络优化的无人机运动控制方法

doi:10.12305/j.issn.1001-506X.2024.05.24

Abstract

Abstract:

In this paper, a model-based motion control method for communication relay unmanned aerial vehicle is proposed to improve the network connectivity and communication performance of ground vehicle formation. The problem of relay unmanned aerial vehicle motion control is solved by considering the unknown multi-user mobility, the impact of the environment on the channel characteristics and the unavailable arrival angle information of the received signal. The method is mainly composed of two parts: (ⅰ) The minimum spanning tree in graph theory is used to construct network connectivity and define communication performance indicators. The network connectivity takes into account the communication links between ground nodes and unmanned aerial vehicles and between ground nodes and ground nodes; (ⅱ) For the communication relay of mobile nodes, a relay unmanned aerial vehicle motion control strategy combining improved particle swarm optimization (PSO) and nonlinear model predictive control (NMPC) is proposed, in which the future position of mobile nodes is predicted by a Kalman filter. The simulation results in a single and complex environment show that the proposed motion control method can drive the unmanned aerial vehicle to reach or track the optimal relay position and improve the network performance. At the same time, it is beneficial to consider the influence of environment on the channel.

Key words: unmanned aerial vehicle, relay communication, motion control, minimum spanning tree, nonlinear model predictive control (NMPC), improved particle swarm optimization (PSO)

CLC Number:

TP301

Cancan TAO, Rui ZHOU. A method of UAV motion control to optimize air-ground relay network[J]. Systems Engineering and Electronics, 2024, 46(5): 1712-1723.

Figures/Tables 11

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References 31

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信道参数	城市郊区	城区	高密度城区	高楼区
α	0.1	0.3	0.5	0.5
β	750	500	300	300
γ	8	5	20	50
a	5.018 8	9.610 1	11.948 0	27.156 2
b	0.351 1	0.159 2	0.135 9	0.122 8
η_LoS/dB	0.1	1.0	1.6	2.3
η_NLoS/dB	21	22	23	34

环境区域	覆盖中心/m		覆盖半径/m
环境区域	X	Y	覆盖半径/m
城市郊区	5 000	5 000	10 000
城区	6 500	4 500	3 500
高密度城区	7 000	3 500	2 000
高楼区	7 700	4 000	600

参数	数值
无人机速度v₀/(m/s)	40
无人机飞行高度h/m	400
转弯率约束(ω_min, ω_max)/(rad/s)	(-0.3, 0.3)
最小转弯半径r_min/m	133.3
地面无人车速度v_g/(m/s)	5
路径衰减因子λ_g	5
放缩因子α	10
基准信号强度S′_t/dBm	-110
权重因子p_c	1e1
权重因子q_c	2
权重因子r_ω	1e5
改进PSO的学习因子c₁	3
改进PSO的学习因子c₂	3
采样周期T_s/s	0.5
滚动优化步数N_r	5

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A method of UAV motion control to optimize air-ground relay network

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