期刊文献+

基于互补滤波的全数字拖靶高度控制系统 被引量:10

Digital Tow Target Altitude Control System Based on Complementary Kalman Filter
下载PDF
导出
摘要 针对掠海恒高飞行拖靶系统在超低空飞行高度控制精度上的技术要求,设计了基于Kalman互补滤波的全数字高度控制系统的结构及控制方案;该方案通过采用Kalman互补滤波来处理高度信号,提高了系统的控制精度;同时,全数字化设计使得系统具有较好的可移植性,提高了使用效率。仿真分析与试飞实践表明:基于互补滤波的数字拖把高度控制系统精度高,使用效率高,且具有较强的抗干扰能力。 In view of the requirements of high height precision for super-low altitude tow target, the structure and the control method of the digital altitude control system are designed, in which the altitude signal is dealt with the algorithm of complementary Kalman filter to improve the control precision. Simulation flight-test results show that the system has the performance of high precision and strong anti-interferences which can fulfill the design requirements. The digital design enables the system to have a better portability and improves the service efficiency.
作者 梅劲松 屈蔷
出处 《南京理工大学学报》 EI CAS CSCD 北大核心 2008年第1期65-68,共4页 Journal of Nanjing University of Science and Technology
关键词 拖靶 超低空飞行 高度控制 KALMAN滤波 tow target super-low altitude flight altitude control Kalman filter
  • 相关文献

参考文献7

  • 1Stephen R N, Dominick A. Longitudinal equilibrium solutions for a towed aircraft and tow cable [ R ]. AIAA 2001:2 001 -4 254.
  • 2Williams P, Sgarioto D, Trivailo P. Optimal control of an aircraft-towed flexible cable system [ J]. Journal of Guidance, Control, and Dynamics, 2006,29 ( 2 ) : 401 - 403.
  • 3Henderson J F, Potjewyd J, Ireland B. The dynamics of an airborne towed target system with active control [J]. Journal of Aerospace Engineering, 1999, 213 (5) : 305 -319.
  • 4Cochran J E Jr. , Innocenti M, No T S, Thukral A. Dynamics and control of maneuverable towed flight vehicles [ J ]. Journal of Guidance, Control, and Dynamics, 1992,15 (5) : 1 245 - 1 252.
  • 5盛安冬,黄飞,刘健,郭治.一种基于多角度的运动目标参数估计新方法[J].南京理工大学学报,2002,26(4):353-356. 被引量:1
  • 6姜雪原,马广富.基于平方根Unscented卡尔曼滤波的无陀螺卫星的姿态估计[J].南京理工大学学报,2005,29(4):399-402. 被引量:6
  • 7王福瑞 等.单片微机测控系统设计大全[M].北京:北京航空航天大学出版社,2001..

二级参考文献9

  • 1Castleman K R.数字图像处理[M].北京:电子工业出版社,1998.423-430.
  • 2Psiaki M L, Martel F, Parimal K P. Three-axis attitude determination via Kalman filtering of magnetometer data [ J].Journal of Guidance, 1990, 13(3): 506 - 514.
  • 3Julier S J, Uhlmann J K, Durrant-Whyte H F. A new approach for filtering nonlinear systems [A]. Proceedings of the American Control Conference [C]. Evanston, IL: American Automatic Control Council, 1995. 1 628- 1 632.
  • 4Julier S J, Uhlmann J K,Durrant-Whyte H F. A new method for the nonlinear transformation of means and covariances in filters and estimator [ J ]. IEEE Transactions on Automatic Control, 2000, 45(3): 477-482.
  • 5Julier S J. The scaled unscented transformation [A]. Proceedings of the American Control Conference [ C]. Evanston,IL: American Automatic Control Council, 2002. 1 t08-1 114.
  • 6Wan E A, van der Merwe R. Kalman filtering and neural networks [M]. New York: John Wiley, 2001.
  • 7van der Merwe R, Wan E A. The square-root Unscented Kalman filter for state and parameter-estimation [ A ]. Proceedings of the International Conference on Acoustics,Speech, and Signal Processing [ C ]. New York: Inst of Electrical and Electronics Engineers, 2001.3 461 - 3 464.
  • 8Grewal M S, Andrews A P. Kalman filtering: theory and practice using MATLAB (2nd ed) [M]. New York: John Wiley, 2001.
  • 9Markley F L, Mortari D. Quaternion attitude estimation using vector observations [J]. The Journal of the Astronautical Sciences, 2000, 48(2, 3): 359-379.

共引文献41

同被引文献43

引证文献10

二级引证文献14

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