Hybrid DE-PEM algorithm for identification of UAV helicopter
Aircraft Engineering and Aerospace Technology
ISSN: 0002-2667
Article publication date: 26 August 2014
Abstract
Purpose
The purpose of this paper is to develop a hybrid algorithm using differential evolution (DE) and prediction error modeling (PEM) for identification of small-scale autonomous helicopter state-space model.
Design/methodology/approach
In this study, flight data were collected and analyzed; MATLAB-based system identification algorithm was developed using DE and PEM; parameterized state-space model parameters were estimated using the developed algorithm and model dynamic analysis.
Findings
The proposed hybrid algorithm improves the performance of the PEM algorithm in the identification of an autonomous helicopter model. It gives better results when compared with conventional PEM algorithm inside MATLAB toolboxes.
Research limitations/implications
This study is applicable to only linearized state-space model.
Practical implications
The identification algorithm is expected to facilitate the required model development for model-based control design for autonomous helicopter development.
Originality/value
This study presents a novel hybrid algorithm for system identification of an autonomous helicopter model.
Keywords
Acknowledgements
This research was supported by the RMGS (Research Matching Grant Scheme), Research Management Center, IIUM, Malaysia. RMGS-09-02
Citation
B. Tijani, I., Akmeliawati, R., Legowo, A., Budiyono, A. and G. Abdul Muthalif, A. (2014), "Hybrid DE-PEM algorithm for identification of UAV helicopter", Aircraft Engineering and Aerospace Technology, Vol. 86 No. 5, pp. 385-405. https://doi.org/10.1108/AEAT-11-2012-0226
Publisher
:Emerald Group Publishing Limited
Copyright © 2014, Emerald Group Publishing Limited