An unmanned helicopter model identification method based on the immune particle swarm optimization algorithm

Ting Ting Yang, Ai Jun Li

科研成果: 期刊稿件会议文章同行评审

2 引用 (Scopus)

摘要

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.

源语言英语
页(从-至)3890-3893
页数4
期刊Applied Mechanics and Materials
347-350
DOI
出版状态已出版 - 2013
活动2013 International Conference on Precision Mechanical Instruments and Measurement Technology, ICPMIMT 2013 - Shenyang, Liaoning, 中国
期限: 25 5月 201326 5月 2013

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