Identification of Helicopter Model using Generalized Back Propagation Through Time

K. Fujarewicz (Poland)


Identification, Nonlinear systems, Gradient methods


This paper deals with a problem of identification 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 of nonlinear plants. Here so called Generalized Back Propagation Through Time (GBPTT) is utilized. This method, derived originally for recurrent neural networks, can be used for any nonlinear dynamical system given as a block diagram. Hence 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 searate measurements or estimation of its parameters.

Important Links:

Go Back