Evaluation of a Helicopter Model Using Generalized Back Propagation Through Time
This paper deals with a problem of evaluation of nonlinear model of the helicopter. The plant is an educational apparatus with two degree of freedom. Whereas the theory of linear identification is well established, there are several possible approaches to identification or evaluation of nonlinear plants. Here so called Generalized Back Propagation Through Time Method (GBPTT) is utilized. This method, derived originally for recurrent neural networks, can be used for any nonlinear dynamical system given as a block diagram. The method is fully structural and, in addition, mnemonic. The results of applying of GBPTT for the helicopter shows that obtained model outperforms the model achieved by separate measurements or estimation of its parameters.
KeywordsBlock Diagram Nonlinear Dynamical System Recurrent Neural Network Sensitivity Model Suboptimal Control
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