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清华大学学报(自然科学版)  2019, Vol. 59 Issue (9): 712-719    DOI: 10.16511/j.cnki.qhdxxb.2019.26.018
  航空航天与工程力学 本期目录 | 过刊浏览 | 高级检索 |
基于在线模型辨识的飞行器多约束复合制导技术
程林1, 张庆振2, 蒋方华1
1. 清华大学 航天航空学院, 北京 100084;
2. 北京航空航天大学 自动化科学与电气工程学院, 北京 100191
Multi-constraint compound reentry guidance based on onboard model identification
CHENG Lin1, ZHANG Qingzhen2, JIANG Fanghua1
1. School of Aerospace Engineering, Tsinghua University, Beijing 100084, China;
2. School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China
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摘要 针对飞行器再入制导问题,该文引入控制变量参数化、积分问题转换和在线模型辨识等技术,提出一种跨周期迭代的可行轨迹预测校正算法,并结合标称轨迹跟踪算法形成一套多约束复合制导方案。利用一种复合高度-速度(height velocity,HV)飞行走廊,将再入轨迹规划问题简化为单调函数寻根问题。为提高射程预测计算效率,引入Gauss-Legendre求积公式,将积分问题转化为函数计算问题。采用递推最小二乘估计方法,收集历史预测信息,实现模型在线辨识功能,并采用跨周期Newton-Raphson方法完成高度权重系数的在线修正。在标称轨迹跟踪器设计的基础上,开展飞行器数值仿真试验,结果表明:基于在线模型辨识的复合制导方法具有显著的速度优势,且具有优异的自主性和自适应能力。
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程林
张庆振
蒋方华
关键词 再入制导复合飞行走廊Gauss求积法递推最小二乘估计模型辨识跨周期参数校正    
Abstract:A period-crossing feasible trajectory planning algorithm for reentry guidance was developed based on control variable parameterization, integral transformations, and onboard model identification. A compound height velocity (HV) corridor simplifies the reentry guidance problem into a root-searching problem. A Gauss integral is introduced to improve the time efficiency of the range prediction with the original integral problem converted into a function calculation problem. The recursive least squares estimation method was used to develop functions for on-board information mining and model identification. The reliable, explicit solution model can easily correct the weight coefficients using the period-crossing Newton-Raphson method. Numerical simulations show that the reentry guidance method based on on-board model identification is much faster, more autonomous and more adaptable than the reference trajectory tracking design method.
Key wordsreentry guidance    compound altitude-velocity corridor    Gaussian integral method    recursive least squares estimation method    model identification    period-crossing parameter correction
收稿日期: 2019-03-06      出版日期: 2019-08-27
基金资助:国家自然科学基金资助项目(11672146)
通讯作者: 蒋方华,副教授,E-mail:jiangfh@tsinghua.edu.cn     E-mail: jiangfh@tsinghua.edu.cn
引用本文:   
程林, 张庆振, 蒋方华. 基于在线模型辨识的飞行器多约束复合制导技术[J]. 清华大学学报(自然科学版), 2019, 59(9): 712-719.
CHENG Lin, ZHANG Qingzhen, JIANG Fanghua. Multi-constraint compound reentry guidance based on onboard model identification. Journal of Tsinghua University(Science and Technology), 2019, 59(9): 712-719.
链接本文:  
http://jst.tsinghuajournals.com/CN/10.16511/j.cnki.qhdxxb.2019.26.018  或          http://jst.tsinghuajournals.com/CN/Y2019/V59/I9/712
  表1 初始再入状态与约束设置
  图1 (网络版彩图)复合 HV走廊
  图2 轨迹在线预测 校正示意图
  表2 3种方法实时性对比
  图3 (网络版彩图)经纬度
  图4 (网络版彩图)高度 速度剖面
  图5 (网络版彩图)权重系数ω 的收敛曲线
  图6 (网络版彩图) 射程偏差和求解时间
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