Control Of An Airship Using Particle Swarm Optimization and Neural Network

被引：4
|
作者：
Jia, Ruting [1 ]
Frye, Michael T. [2 ]
Qian, Chunjiang [1 ]
机构：
[1] Univ Texas San Antonio, Dept Elect & Comp Engn, San Antonio, TX 78249 USA
[2] Univ Incarnate Word, Dept Engn, San Antonio, TX 78249 USA
来源：
2009 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS (SMC 2009), VOLS 1-9 | 2009年
基金：
美国国家科学基金会;
关键词：
Particle swarm optimization; dynamic neural network model; real time optimal control;
D O I：
10.1109/ICSMC.2009.5346862
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
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.
引用
收藏
页码：1809 / +
页数：2
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