This paper considers in flight parameter identification and icing location detection of the aircraft in a more common time-varying\nnature. In particular, ice accumulation is modeled as a continuous process, and the effect of the ice upon aircraft dynamics is to\nbe accreted with time. Time-varying case of the Hinf algorithm is implemented to provide in flight estimate of aircraft dynamic\nparameters, and the estimated results are delivered to a probabilistic neural network to decide icing location of the aircraft; an\nexcitation measure of the aircraft is also adopted in the network input layer. A database corresponding to different icing cases and\nseverities was generated for the training and test of the detection network. Based on the test results, the icing detection framework\npresented in this paper is believed to be with promising applicableness for our further studies.
Loading....