Abstract
In this paper, Cascade Forward Back Propagation (CFBP) based on neural network is proposed for the estimation of lateral and directional derivatives of an aircraft. The proposed technique is applied on the simulated flight data of research aircraft ‘HANSA’ to extract derivatives of lateral and directional motion. The results obtained using the proposed technique are compared with results obtained using existing Feed Forward Neural Network (FFNN) and Elman Network Technique (ENT) The derivatives are also estimated using the simulated data with 5 percent and 10 percent noise to check the reliability of the proposed technique and working in real flight conditions. It is observed that Cascade Forward Back Propagation (CFBP) has great capabilities to estimate derivatives of an aircraft.
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