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基于模糊神經(jīng)網(wǎng)絡(luò )的無(wú)人機數據傳輸時(shí)延控制模型
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廣西工業(yè)職業(yè)技術(shù)學(xué)院

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TN911

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Data Transmission Delay Control Model for Unmanned Aerial Vehicle Based on Fuzzy Neural NetworkWeiJinri1,SQinXi2
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    摘要:

    傳輸信道狀態(tài)若是處于擁塞狀態(tài),會(huì )使得無(wú)人機數據傳輸時(shí)延大幅度增加,所以構建基于模糊神經(jīng)網(wǎng)絡(luò )的無(wú)人機數據傳輸時(shí)延控制模型。考慮直射、散射和反射等現象確定無(wú)人機數據傳輸信道,計算無(wú)人機數據傳輸信道傳輸時(shí)延,綜合能量消耗、時(shí)延等因素判斷無(wú)人機數據傳輸信道是否處于擁塞狀態(tài)。利用基于模糊神經(jīng)網(wǎng)絡(luò )的時(shí)延控制模型生成時(shí)延控制指令,通過(guò)擴頻調制、擁塞調度和隊列管理等步驟,實(shí)現無(wú)人機數據傳輸時(shí)延控制。通實(shí)驗結果表明,在該模型控制下無(wú)人機數據傳輸時(shí)延達到預期水平,控制誤差約為0.03s,且未對數據傳輸進(jìn)程產(chǎn)生明顯不利影響,控制效果更好。

    Abstract:

    If the transmission channel state is in the congestion state, the UAV data Transmission delay will increase significantly. Therefore, the 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 UAV data transmission channel is judged to be congested by combining the factors such as energy consumption and delay. 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 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 0.03s, and there is no obvious adverse impact on the data transmission process, so the control effect is better.

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韋金日,覃希.基于模糊神經(jīng)網(wǎng)絡(luò )的無(wú)人機數據傳輸時(shí)延控制模型計算機測量與控制[J].,2024,32(6):97-103.

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歷史
  • 收稿日期:2023-06-05
  • 最后修改日期:2023-07-17
  • 錄用日期:2023-07-18
  • 在線(xiàn)發(fā)布日期: 2024-06-18
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