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      [1]康繼芝,張士峰,胡鋮.氣動參數在線辨識在火箭助推段制導中的應用[J].哈爾濱工程大學學報,2020,41(7):1052-1058.[doi:10.11990/jheu.201901089]
       KANG Jizhi,ZHANG Shifeng,HU Cheng.Application of aerodynamic parameter online identification in rocket ascent guidance[J].hebgcdxxb,2020,41(7):1052-1058.[doi:10.11990/jheu.201901089]
      點擊復制

      氣動參數在線辨識在火箭助推段制導中的應用(/HTML)
      分享到:

      《哈爾濱工程大學學報》[ISSN:1006-6977/CN:61-1281/TN]

      卷:
      41
      期數:
      2020年7期
      頁碼:
      1052-1058
      欄目:
      出版日期:
      2020-07-05

      文章信息/Info

      Title:
      Application of aerodynamic parameter online identification in rocket ascent guidance
      作者:
      康繼芝 張士峰 胡鋮
      國防科技大學 空天科學學院, 湖南 長沙 410073
      Author(s):
      KANG Jizhi ZHANG Shifeng HU Cheng
      College of Aerospace Science and Engineering, National University of Defense Technology, Changsha 410073, China
      關鍵詞:
      攝動制導小擾動量氣動參數辨識擴展卡爾曼濾波限定記憶最小二乘法
      分類號:
      V488.1
      DOI:
      10.11990/jheu.201901089
      文獻標志碼:
      A
      摘要:
      為減小氣動參數擾動對火箭助推段的影響,提高制導精度365英超体育投注,本文將火箭飛行過程中的氣動參數擾動量視為攝動制導中的小擾動量,對傳統攝動方程進行改進。采用擴展Kalman濾波方法對氣動參數擾動量進行辨識,再利用限定記憶遞推最小二乘法基于辨識結果進行預測,將預測結果用于下一階段的攝動制導計算365英超体育投注,構建了“辨識—預測—計算”迭代更新的在線辨識模型365英超体育投注。本文設計的擴展Kalman濾波器辨識效果較好365英超体育投注,收斂時間10 s左右,辨識精度10%以內。設計的結合氣動參數在線辨識的攝動制導方案相對于傳統方案,能有效降低終端狀態偏差。Monte Carlo打靶結果表明改進攝動制導方案對偏差的魯棒性增強,彈道收斂性更好365英超体育投注。本文將氣動參數在線辨識用于火箭助推段的攝動制導,降低了氣動參數擾動對制導精度的影響,在一定程度上提高了攝動制導的性能,對工程實踐具有參考作用。

      參考文獻/References:

      [1] 陳克俊, 劉魯華, 孟云鶴. 遠程火箭飛行動力學與制導[M]. 北京:國防工業出版社, 2014:50, 256-260. CHEN Kejun, LIU Luhua, MENG Yunhe. Launch vehicle flight dynamics and guidance[M]. Beijing:National Defense Industry Press, 2014:50, 256-260.
      [2] 陳克俊. 載人飛船上升段攝動制導方法探討[J]. 航天控制, 1992(2):1-5. CHEN Kejun. An approach to the concept of perturbation guidance of manned spaceraft during ascent phase[J]. Aerospace control, 1992(2):1-5.
      [3] 黃小平, 王巖. 卡爾曼濾波原理及應用——MATLAB仿真[M]. 北京:電子工業出版社, 2015:2-5. HUANG Xiaoping, WANG Yan. Kalman filter and its application[M]. Beijing:Publishing House of Electronics Industry, 2015:2-5.
      [4] KANDEPU R, FOSS B, IMSLAND L. Applying the unscented Kalman filter for nonlinear state estimation[J]. Journal of process control, 2008, 18(7/8):753-768.
      [5] 涂海峰, 賈生偉, 陽豐俊, 等. 基于無跡卡爾曼濾波的巡飛彈氣動參數在線辨識方法[J]. 航天控制, 2018, 36(5):14-18. TU Haifeng, JIA Shengwei, YANG Fengjun, et al. Loitering munition aerodynamic parameter online identification method based on unscented Kalman filter[J]. Aerospace control, 2018, 36(5):14-18.
      [6] 馮鵬, 鄒世開. 卡爾曼濾波器UD分解濾波算法的改進[J]. 遙測遙控, 2005, 26(1):10-14. FENG Peng, ZOU Shikai. Improvement of the UD covariance factorization algorithm of Kalman filter[J]. Telemetry & telecontrol, 2005, 26(1):10-14.
      [7] 梁子璇, 任章. 基于在線氣動參數修正的預測制導方法[J]. 北京航空航天大學學報, 2013, 39(7):853-857. LIANG Zixuan, REN Zhang. Predictive reentry guidance with aerodynamic parameter online correction[J]. Journal of Beijing University of Aeronautics and Astronautics, 2013, 39(7):853-857.
      [8] KUMAR R, GANGULI R, OMKAR S N, et al. Rotorcraft parameter identification from real time flight data[J]. Jounal of aircaft, 2008, 45(1):333-341.
      [9] 崔乃剛, 盧寶剛, 傅瑜, 等. 基于卡爾曼濾波的再入飛行器氣動參數辨識[J]. 中國慣性技術學報, 2014, 22(6):755-758. CUI Naigang, LU Baogang, FU Yu, et al. Aerodynamic parameter identification of a reentry vehicle based on Kalman filter method[J]. Journal of Chinese inertial technology, 2014, 22(6):755-758.
      [10] 余舜京, 程艷青, 錢煒褀. 跨聲速氣動參數在線辨識方法研究[J]. 宇航學報, 2011, 32(6):1211-1216. YU Shunjing, CHENG Yanqing, QIAN Weiqi. Research on transonic aerodynamic parameter online identification[J]. Journal of astronautics, 2011, 32(6):1211-1216.
      [11] GARCIA-VELO J, WALKER B K. Aerodynamic parameter estimation for high-performance aircraft using extended Kalman filtering[J]. Journal of guidance, control, and dynamics, 1997, 20(6):1257-1260.
      [12] CHOWDHARY G, JATEGAONKAR R. Aerodynamic parameter estimation from flight data applying extended and unscented Kalman filter[C]//AIAA Atmospheric Flight Mechanics Conference and Exhibit. Colorado, 2006.
      [13] 趙漢元. 飛行器再入動力學和制導[M]. 長沙:國防科技大學出版社, 1997. ZHAO Hanyuan. Fight vehicle reentry dynamics and guidance[M]. Changsha:National University of Defense Technology Press, 1997.
      [14] 張遷, 許志, 李新國. 一種多級全固體運載火箭上升段自主制導方法[J]. 宇航學報, 2019, 40(1):19-28. ZHANG Qian, XU Zhi, LI Xinguo. An autonomous ascent guidance method for multi-stage solid launch vehicles[J]. Journal of astronautics, 2019, 40(1):19-28.
      [15] 徐光, 徐楚韶. 參數估計算法的研究[J]. 武漢科技大學學報(自然科學版), 2000, 23(4):341-343. XU Guang, XU Chushao. Study of the algorithm for parameter estimation[J]. Journal of Wuhan University of Science and Technology (natural science edition), 2000, 23(4):341-343.
      [16] 李訓艷, 周玉國, 逯倩倩. 限定記憶法辨識帶鋼熱鍍鋅退火爐模型參數[J]. 計算機時代, 2012(1):21-23. LI Xunyan, ZHOU Yuguo, LU QianQian. Identification of strip steel galvanized annealing furnace model parameters using fixed memory method[J]. Computer era, 2012(1):21-23.

      備注/Memo

      備注/Memo:
      收稿日期:2019-01-31。
      基金項目:國家自然科學基金項目(11804221).
      作者簡介:康繼芝,男,碩士研究生;張士峰,男,教授,博士生導師.
      通訊作者:張士峰,E-mail:kangjizhi5634@163.com
      更新日期/Last Update: 2020-08-15
      365英超体育投注

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