An Unmanned Helicopter Model Identification Method based on the Immune Particle Swarm Optimization Algorithm
- https://doi.org/10.2991/iccsee.2013.696How to use a DOI?
- model identification, immune PSO, unmanned helicopter
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.
- © 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/).
Cite this article
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 - https://doi.org/10.2991/iccsee.2013.696 ID - Yang2013/03 ER -