Turbojet modeling in windmilling based on radial basis function networks

The windmilling process of missile turbojet is such a complex nonlinear process that to obtain its dynamic model theoretically is very difficult, because the compressor works in expending mode (non-normal operating mode) in this condition. Considering the great capacity of handling nonlinearity of the neural network, an experimental model of the windmilling process using radial basis function networks (RBFN) was established and a good precision through selecting the parameters and the training samples of the network properly was gained. The neural network is of great value for computing the point of ignition or simulating the windmilling process.