Abstract
State space identification of aircraft flight models is carried out in this work. The identification results in estimation of derivatives of stability and control matrices and also biases of sensors. The identification procedure is based on likelihood function minimization based on Kalman filter and stochastic approximation. The least square method determines initial values for unknown parameter of state space models which are important for identification of models. The results obtained for models are presented. The decoupled longitudinal and lateral models of a small six seat aircraft are utilized in this work.
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