摘要
利用实测到的发动机飞行试验数据作为学习样本 ,采用径向基函数 ( RBF)神经网络建立了发动机的辨识模型。利用这种方法对不同飞行高度发动机的参数进行了辨识 ,并与几种 BP网络进行了比较。研究结果表明 :这种方法具有训练时间短、学习速度快、辨识精度高等优点。
The identification model of aeroengine based on the Radial Basis Function network is set up by using the measured flight tests data as learning stylebook.The parameters of engine are identified at different flight heights by this method.The network is also compared with several Back Propagation networks.The results show that this method has the advantage of faster learning rate,higher identifying precision and better real time ability.It can be used on the engine on line identification.
出处
《航空动力学报》
EI
CAS
CSCD
北大核心
2000年第2期205-208,共4页
Journal of Aerospace Power
