人工神经网络在飞机下沉速度控制中的应用  

Application of Artificial Neural Network in Aircraft Sinking Speed Control

作　　者：解丰安 舒成辉[1] 蒋启登[1] Xie Feng’an;Shu Chenghui;Jiang Qideng(China Flight Test Establishment,Xi’an 710089,China)

机构地区：[1]中国飞行试验研究院,陕西西安710089

出　　处：《航空科学技术》2024年第4期90-96,共7页Aeronautical Science & Technology

摘　　要：下沉速度是指飞机着陆接地时刻其重心的垂向速度,它直接关系到飞机起落装置在接地时所受到的载荷大小。在考核飞机起落架强度、刚度的着陆试验中,国军标对飞机的下沉速度有具体的要求,但在实际操作中,由于各种外部因素的干扰,飞行员很难利用现有的手段精准操纵飞机达到标准要求的下沉速度。本文通过合理分析,选取了几个影响陆基飞机下降速度的飞行参数,并将这些参数的实测飞行数据作为MATLAB人工神经网络模型的输入与输出,得到了较好的预测结果,探索了控制陆基飞机下沉速度的新思路与新方法。The sinking speed refers to the vertical speed of the center of gravity of the aircraft at the time of landing and grounding,which is directly related to the load of the aircraft landing device when grounding.In the landing test to assess the strength and rigidity of the aircraft landing gear,the national military standard has specific requirements for the sinking speed of the aircraft,but in actual operation,due to the interference of various external factors,it is difficult for pilots to use existing means to accurately control the aircraft to achieve the sinking speed required by the standard.Through reasonable analysis,several flight parameters affecting the descent speed of land-based aircraft are selected,and the measured flight data of these parameters are used as the input and output of MATLAB artificial neural network model,and good prediction results are obtained,and new ideas and methods for controlling the sinking speed of land-based aircraft are explored.

关 键 词：着陆试验 飞机下沉速度 着陆飞行控制方法 人工神经网络 

分 类 号：V217.32[航空宇航科学与技术—航空宇航推进理论与工程]