期刊文献+

优化的卡尔曼滤波算法在船用逆变器中的应用

The Improvement of Kalman Filtering Algorithm Apply in The Inverter of Ship
下载PDF
导出
摘要 由于船用逆变器的输入电力主要来源于发电机组,谐波含量较高,谐波严重威胁电力环境,甚至威胁到航行安全及船员生命安全,所以在船用逆变器必须对谐波进行处理。该文介绍了一种简化了卡尔曼滤波算法,使其在数字控制系统中既用较为简单的实现算法保证了运算的精度,又起到了滤波的效果,并通过实际的试验数据对该滤波算法进行了验证。 Because of the input electric power of inverter is generator unit on the ship. scale of harmonic is higher.The harmonic threaten the safety of seaway and seaman's life,so we must deal with the harmonic of inverter on the ship. In this paper,we introduce a simplify Kalman filtering algorithm,it achieve briefness,and effect of filtering is marked.This Algorithm is proved by practical test data.
作者 张蕾
机构地区 中船重工第
出处 《科技创新导报》 2015年第19期213-214,共2页 Science and Technology Innovation Herald
关键词 卡尔曼滤波 逆变器 谐波 Kalman filtering Inverter Harmonic
  • 相关文献

参考文献4

二级参考文献23

  • 1于九祥.微机保护中卡尔曼滤波模型参数的选择[J].电力系统自动化,1993,17(2):26-33. 被引量:4
  • 2邓自立,毛琳,高媛.多传感器最优信息融合稳态Kalman滤波器[J].科学技术与工程,2004,4(9):743-748. 被引量:8
  • 3董峰,金宏斌,白晶.用Visual C++仿真实现卡尔曼滤波[J].微计算机信息,2005,21(06Z):147-149. 被引量:8
  • 4樊恩,聂明新.采用稳态Kalman滤波器简化Kalman滤波器的计算[J].武汉理工大学学报(信息与管理工程版),2005,27(5):272-274. 被引量:3
  • 5Kalman R E. A new approach to linear filtering and prediction problems[J]. Transactions of the ASME- Journal of Basic Engineering, 1960, 82 (Series D): 35-45.
  • 6Kalman R E. New methods and results in linear filtering and prediction theory[J]. Transactions of the ASME-Journal of Basic Engineering, 1961, 83 (Series D): 95-108.
  • 7Lerro D, Bar-Shalom Y. Tracking with debiased consistent converted measurements versus EKF [J]. IEEE Transactions on Aerospace and Electronic Systems, 1993, 29(3): 1015-1022.
  • 8Julier S, Uhlmann J, Durrant-Whyte H F. A new method for the nonlinear transformation of means and covariances in filters and estimators[J]. IEEE Transactions on Automatic Control, 2000, 45(3): 477-481.
  • 9Gustafsson F, Gunnarsson F, Bergman N, et al. Particle filters for positioning, navigation and tracking [J]. IEEE Transactions on Signal Processing, 2002, 50(2): 425-437.
  • 10De-Freitas J F G, Niranjan M, Gee A H, et al. Sequential Monte Carlo methods to train neural net- work models [J]. Neural Computation, 2000, 12 (4): 955-993.

共引文献21

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部