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Simulation and system identification of helicopter dynamics using support vector regression

Published online by Cambridge University Press:  27 January 2016

S. Manso
S. Manso*
Affiliation:
Defence Science & Technology Organisation, Fishermens Bend, Australia
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Abstract

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This paper provides an overview of techniques developed for the application of support vector regression in the domain of simulation and system identification of helicopter dynamics. A generic high fidelity FLIGHTLAB helicopter model is used to train and validate a number of pitch response SVR models. These models are then trained using flight data from a Sikorsky Seahawk helicopter. The SVR simulation results show significant promise in the ability to represent aspects of a helicopter’s dynamics at a high fidelity. To achieve this, it is important to provide the SVR kernel with knowledge of past inputs that encompass the delay characteristics of the helicopter dynamic system. In this case, the use of nonlinear auto regressive eXogenous input network architecture achieves this goal. Good performance was achieved using input data that encompassed between 300 to 500ms worth of historic response.

Information

Type
Research Article
Information
The Aeronautical Journal , Volume 119 , Issue 1222: A Rotorcraft Special Issue , December 2015 , pp. 1541 - 1560
Copyright
Copyright © Royal Aeronautical Society 2015

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