Linear Model Extraction of a Launch Vehicle by System Identification based on Six Degrees of Freedom Simulation

M. Tayefi, J. Roshanian, and M. Bahrami


Aerospace launch vehicle, system identification, six degrees of freedom simulation, Kalman filter


The transfer functions of the aerospace launch vehicle can be extracted using well-known linearization methodology. This paper presents an alternative to obtain the transfer functions via closed-loop identification using six degrees of freedom nonlinear simulation software. The vehicle is characterized by high nonlinearity, open loop instability and time-varying behaviours. The model structure with some unknown parameters is obtained after mathematical modeling, thus the case of our problem is a parameter identification one. Time-variant parameters are estimated by Kalman filter approach with the aid of ARX model structure.

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