TY - JOUR
T1 - 基于凸优化和 LQR 的火箭返回轨迹跟踪制导
AU - Wu, Jie
AU - Zhang, Cheng
AU - Li, Miao
AU - Xiong, Fenfen
N1 - Publisher Copyright:
© 2022 Beijing University of Aeronautics and Astronautics (BUAA). All rights reserved.
PY - 2022/11
Y1 - 2022/11
N2 - For the powered descent phase of the reusable launch vehicle, various strict process constraints, terminal constraints and requirements on fuel saving exist, which bring great challenges to the guidance. This paper proposes a trajectory tracking guidance method based on convex optimization and linear quadratic regulator (LQR). The improved receding horizon convex optimization method is used to track the reference velocity of the rocket without requiring accurate thrust control input, which greatly simplifies the optimization model, and thus saves the computational cost of solving the optimal control problem. Meanwhile, the fuel is reduced as far as possible under various initial errors and model errors. On the other hand, the LQR technique is used to track the position of the rocket with high precision. The simulation results show that compared with the traditional LQR tracking guidance method, the proposed method can obtain comparable tracking accuracy, while greatly reducing fuel consumption. And compared to the existing receding horizon convex optimization, the proposed method can evidently reduce the computational cost and improve reliability.
AB - For the powered descent phase of the reusable launch vehicle, various strict process constraints, terminal constraints and requirements on fuel saving exist, which bring great challenges to the guidance. This paper proposes a trajectory tracking guidance method based on convex optimization and linear quadratic regulator (LQR). The improved receding horizon convex optimization method is used to track the reference velocity of the rocket without requiring accurate thrust control input, which greatly simplifies the optimization model, and thus saves the computational cost of solving the optimal control problem. Meanwhile, the fuel is reduced as far as possible under various initial errors and model errors. On the other hand, the LQR technique is used to track the position of the rocket with high precision. The simulation results show that compared with the traditional LQR tracking guidance method, the proposed method can obtain comparable tracking accuracy, while greatly reducing fuel consumption. And compared to the existing receding horizon convex optimization, the proposed method can evidently reduce the computational cost and improve reliability.
KW - convex optimization
KW - linear quadratic regnlator
KW - powered decent phase
KW - reusable launch vehicle
KW - trajectory tracking guidance
UR - http://www.scopus.com/inward/record.url?scp=85144541712&partnerID=8YFLogxK
U2 - 10.13700/j.bh.1001-5965.2021.0084
DO - 10.13700/j.bh.1001-5965.2021.0084
M3 - 文章
AN - SCOPUS:85144541712
SN - 1001-5965
VL - 48
SP - 2270
EP - 2280
JO - Beijing Hangkong Hangtian Daxue Xuebao/Journal of Beijing University of Aeronautics and Astronautics
JF - Beijing Hangkong Hangtian Daxue Xuebao/Journal of Beijing University of Aeronautics and Astronautics
IS - 11
ER -