基于MADDPG的分布式测控网络群切换算法

doi:10.12305/j.issn.1001-506X.2025.06.31

Abstract

Abstract:

Affected by the navigation denial in special environments such as war, node mobility and environmental interference, rapid topology reconfiguration of the measurement and control network is the key to ensure continuous positioning. In order to solve the above problems, a distributed multi-agent measurement and control network group switching algorithm based on multi-agent deep deterministic policy gradient (MADDPG) for the scenario of multi system unmanned cluster measurement and control network is proposed. This algorithm employs a partially observable Markov decision process model and considers minimum connectivity, energy consumption and measurement and control precision to design the reward function, and constructs a reliable measurement and control localization system. Simulation results show that the algorithm is feasible and effective in different interference environments to effectively resist external interference, ensure the normal operation of measurement, control and localization, and improve the switching success rate to more than 12% compared with traditional switching algorithms.

Key words: topology reconfiguration, group switching, measurement and control positioning, partially observable Markov decision, minimum connectivity

CLC Number:

TN393

Huilin WANG, Shengli LIU, Anhong XIE, Lidong ZHU. Group switching algorithm for distributed measurement and control network based on MADDPG[J]. Systems Engineering and Electronics, 2025, 47(6): 2036-2046.

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References 32

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网络类型	速度/(km/min)	相对高度/km
低轨卫星	-	1 200
高空气球	[20, 30]	[200, 210]
无人机	[15, 30]	[50, 60]
无人飞艇	[5, 8]	[10, 20]
无人车	0	0
无人船	0	0

网络参数	符号	数值
天线发射功率/mW	P_t	60
光速/(m/s)	c	3×10⁸
载波频率/GHz	f	23
传输速率/Mbps	R	11
数据包大小/bit	B	512
天线转向能耗/(J/(°))	γ	0.001
其他固有的能源消耗/J	E_u^c(t)	80

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Group switching algorithm for distributed measurement and control network based on MADDPG

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