Title: Modelling a small-size unmanned helicopter using optimal estimation in the frequency domain

Authors: Dalei Song, Juntong Qi, Lei Dai, Jianda Han, Guangjun Liu

Addresses: State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy Sciences, Shenyang, Liaoning Province, China; Graduate School of Chinese Academy of Sciences, Beijing, China. ' State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy Sciences, Shenyang, Liaoning Province, China; Graduate School of Chinese Academy of Sciences, Beijing, China. ' State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy Sciences, Shenyang, Liaoning Province, China; Graduate School of Chinese Academy of Sciences, Beijing, China. ' State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy Sciences, Shenyang, Liaoning Province, China. ' Department of Aerospace Engineering, Ryerson University, Toronto, Ontario M5B 2K3, Canada

Abstract: In this paper, a semi-decoupled state-space model of a small-size helicopter is developed for hovering conditions in order to simplify the model identification process. An enhanced identification algorithm in frequency domain is proposed and implemented to estimate the parameters in the state-space model using real flight data collected from a SERVOHELI-40 small-size unmanned helicopter. The accuracy of the identified model is verified by simulation in time domain, using a different set of hovering flight data. The results have shown the accuracy of the developed semi-decoupled model and the effectiveness of the proposed optimal estimation algorithm in frequency domain.

Keywords: small-size helicopters; unmanned helicopters; helicopter modelling; optimal estimation; hovering conditions; model identification; frequency domain; unmanned flight; state-space models; simulation.

DOI: 10.1504/IJISTA.2010.030191

International Journal of Intelligent Systems Technologies and Applications, 2010 Vol.8 No.1/2/3/4, pp.70 - 85

Published online: 11 Dec 2009 *

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