基于凸优化和 LQR 的火箭返回轨迹跟踪制导

Translated title of the contribution: Rocket return trajectory tracking guidance based on convex optimization and LQR

Jie Wu, Cheng Zhang, Miao Li, Fenfen Xiong*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

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.

Translated title of the contributionRocket return trajectory tracking guidance based on convex optimization and LQR
Original languageChinese (Traditional)
Pages (from-to)2270-2280
Number of pages11
JournalBeijing Hangkong Hangtian Daxue Xuebao/Journal of Beijing University of Aeronautics and Astronautics
Volume48
Issue number11
DOIs
Publication statusPublished - Nov 2022

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