基于RBF网络的火箭发动机动态过程建模

ROCKET ENGINE DYNAMIC PROCESS MODELING BASED ON RBFN

提出了基于径向基函数神经网络（ＲＢＦＮ）的火箭发动机动态过程建模，仿真计算表明：采用ＲＢＦＮ建模，可以达到很好的逼近精度，而且网络训练速度大大加快，可以更好地适应实时状态监控和故障诊断，有实际的工程运用价值。

Rocket engine(RE)dynamic process was modeled by radial basis function networks(RBFN).Using RBFN for modeling can gain a good precision and make the learning speed of networks rapid.So the method presented will be beter to adapt to the state online detection and fault diagnosis.It is practical in the actual engineering