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基于萤火虫优化神经网络算法的气浮台自动调平衡研究

周国光 金光 徐伟 朴永杰 常琳

周国光, 金光, 徐伟, 朴永杰, 常琳. 基于萤火虫优化神经网络算法的气浮台自动调平衡研究[J]. 空间科学学报, 2021, 41(3): 483-490. doi: 10.11728/cjss2021.03.483
引用本文: 周国光, 金光, 徐伟, 朴永杰, 常琳. 基于萤火虫优化神经网络算法的气浮台自动调平衡研究[J]. 空间科学学报, 2021, 41(3): 483-490. doi: 10.11728/cjss2021.03.483
ZHOU Guoguang, JIN Guang, XU Wei, PIAO Yongjie, CHANG Lin. Automatic Balancing Control of Air-bearing Simulator Based on Firefly Algorithm Improved Neural Network[J]. Journal of Space Science, 2021, 41(3): 483-490. doi: 10.11728/cjss2021.03.483
Citation: ZHOU Guoguang, JIN Guang, XU Wei, PIAO Yongjie, CHANG Lin. Automatic Balancing Control of Air-bearing Simulator Based on Firefly Algorithm Improved Neural Network[J]. Journal of Space Science, 2021, 41(3): 483-490. doi: 10.11728/cjss2021.03.483

基于萤火虫优化神经网络算法的气浮台自动调平衡研究

doi: 10.11728/cjss2021.03.483
基金项目: 

吉林省省级产业创新专项项目(2018C18076)和吉林省优秀青年人才基金项目(20180520216JH)共同资助

详细信息
    作者简介:

    周国光,E-mail:zgg1995@qq.com

  • 中图分类号: V524

Automatic Balancing Control of Air-bearing Simulator Based on Firefly Algorithm Improved Neural Network

  • 摘要: 为了利用气浮台在地面精准演示分布式多星组网技术及验证多模式高分成像过程,提出一种基于改进型BP神经网络PID控制的气浮台快速自动调平衡算法.针对以往算法调平时间较长、容易得到非最优解的问题,引入仿生萤火虫算法对神经网络初始权值进行优化,提高了算法的收敛速度和稳定性.基于构建的三轴气浮台运动学和动力学模型,通过仿真实验验证了优化算法对自动调平衡具有良好的控制效果,满足多星地面仿真的调平衡要求.

     

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出版历程
  • 收稿日期:  2019-10-30
  • 修回日期:  2020-03-11
  • 刊出日期:  2021-05-15

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