DocumentCode
2581178
Title
Control of an airship using particle swarm optimization and neural network
Author
Jia, Ruting ; Frye, Michael T. ; Qian, Chunjiang
Author_Institution
Electr. & Comput. Eng. Dept., Univ. of Texas at San Antonio, San Antonio, TX, USA
fYear
2009
fDate
11-14 Oct. 2009
Firstpage
1809
Lastpage
1814
Abstract
The objective of this paper is to design an optimized controller for the tri-turbofan airship model. In lieu of using the traditional controller analysis method, the particle swarm optimization algorithm for controller optimization has been implemented. For more accurate results, this research used an updated neural network model to approximate the actual tri-turbofan airship dynamics. The effectiveness of the PSO algorithm will be shown by the simulation in an updated neural network model, compared to a linear model of the tri-turbofan model.
Keywords
aerospace computing; aircraft control; control system analysis; control system synthesis; neural nets; optimal control; particle swarm optimisation; PSO algorithm; controller optimization; neural network; particle swarm optimization; real time optimal control; tri-turbofan airship dynamics; tri-turbofan airship model; Cellular phones; Design engineering; Design optimization; Evolutionary computation; Neural networks; Optimal control; Particle swarm optimization; Surveillance; USA Councils; Vehicle dynamics; Particle swarm optimization; dynamic neural network model; real time optimal control;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems, Man and Cybernetics, 2009. SMC 2009. IEEE International Conference on
Conference_Location
San Antonio, TX
ISSN
1062-922X
Print_ISBN
978-1-4244-2793-2
Electronic_ISBN
1062-922X
Type
conf
DOI
10.1109/ICSMC.2009.5346862
Filename
5346862
Link To Document