Control Of An Airship Using Particle Swarm Optimization and Neural Network

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—Particle swarm optimization, dynamic neural network model, real time optimal control

DOI: 10.1109/ICSMC.2009.5346862

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Cite this paper

@inproceedings{Jia2009ControlOA, title={Control Of An Airship Using Particle Swarm Optimization and Neural Network}, author={Ruting Jia and Michael T. Frye and Chunjiang Qian}, booktitle={SMC}, year={2009} }