An Unmanned Helicopter Model Identification Method based on the Immune Particle Swarm Optimization Algorithm

DOI

10.2991/iccsee.2013.696How to use a DOI?

Keywords

model identification, immune PSO, unmanned helicopter

Abstract

An unmanned helicopter dynamic model identification method based on immune particle swarm optimization (PSO) algorithm is approved in this paper. In order to improve the search efficiency of PSO and avoid the premature convergence, the PSO algorithm is combined with the immune algorithm. The unmanned helicopter model parameters are coded as particle, the error of flight test and math simulation model is objective function, and the dynamic model of unmanned helicopter is identified. The simulation result shows that the method has high identification precision and can realistically reflect the dynamic characteristics.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Tingting Yang
AU  - Aijun Li
PY  - 2013/03
DA  - 2013/03
TI  - An Unmanned Helicopter Model Identification Method based on the Immune Particle Swarm Optimization Algorithm
BT  - Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013)
PB  - Atlantis Press
SP  - 2790
EP  - 2792
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccsee.2013.696
DO  - 10.2991/iccsee.2013.696
ID  - Yang2013/03
ER  -