基于模糊神经网络的无人机数据传输时延控制模型  

Data Transmission Delay Control Model for UAV Based on Fuzzy Neural Network

作　　者：韦金日[1] 覃希[2] WEI Jinri;QIN Xi(Continuous Education College,Guangxi Industrial Vocational and Technical College,Nanning 530001,China;School of Computer,Guangxi University,Nanning 530004,Chin)

机构地区：[1]广西工业职业技术学院继续教育学院,南宁530001 [2]广西大学计算机与电子信息学院,南宁530004

出　　处：《计算机测量与控制》2024年第6期97-103,共7页Computer Measurement &Control

摘　　要：传输信道状态若是处于拥塞状态,会使得无人机数据传输时延大幅度增加,所以构建基于模糊神经网络的无人机数据传输时延控制模型;考虑直射、散射和反射等现象确定无人机数据传输信道,计算无人机数据传输信道传输时延,综合能量消耗、时延等因素判断无人机数据传输信道是否处于拥塞状态;利用基于模糊神经网络的时延控制模型生成时延控制指令,通过扩频调制、拥塞调度和队列管理等步骤,实现无人机数据传输时延控制;实验结果表明,在该模型控制下无人机数据传输时延达到预期水平,控制误差约为0.03 s,且未对数据传输进程产生明显不利影响,控制效果更好。If transmission channel state is in congestion state,unmanned aerial vehicle(UAV)data transmission delay will increase significantly.Therefore,a UAV data transmission delay control model based on fuzzy neural network is constructed.The UAV data transmission channel is determined by considering the phenomena of direct radiation,scattering and reflection,and the transmission delay of the UAV data transmission channel is calculated.the energy consumption and delay are comprehensively judged whether the UAV data transmission channel is in a congestion state.The delay control command is generated by the delay control model based on fuzzy neural network,and the UAV data transmission delay control is achieved through the spread spectrum modulation,congestion scheduling,queue management and other steps.The experimental results show that under the control of this model,the data transmission time of UAV reaches the expected level,the control error is about 0.03 s,and there is no obvious abnormal impact on the data transmission process,achieving a better control effect.

关 键 词：模糊神经网络 无人机数据 传输时延 时延控制模型 拥塞状态 能量消耗 

分 类 号：TN911[电子电信—通信与信息系统]