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

Ting Ting Yang; Ai Jun Li

doi:10.4028/www.scientific.net/AMM.347-350.3890

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 347-350An Unmanned Helicopter Model Identification Method...

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

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.

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Periodical:

Applied Mechanics and Materials (Volumes 347-350)

Pages:

3890-3893

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.347-350.3890

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Online since:

August 2013

Authors:

Ting Ting Yang, Ai Jun Li

Keywords:

Immune PSO, Model Identification, Unmanned Helicopter

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References

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