Journal of Astronautics ›› 2022, Vol. 43 ›› Issue (8): 1029-1039.doi: 10.3873/j.issn.1000-1328.2022.08.005

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Sequential Convex Optimization Method for Lunar Landing During Powered Descent Phase

DENG Yanpeng, MU Rongjun, PENG Na, WU Peng   

  1. 1. School of Astronautics, Harbin Institute of Technology, Harbin 150001, China; 2. Shanghai Aerospace Electronic Technology Institute, Shanghai 201109, China
  • Received:2022-01-19 Revised:2022-05-15 Online:2022-08-15 Published:2022-08-15

Abstract: Aiming at the problem that it is difficult to estimate and compensate the time varying inertial acceleration and gravitational acceleration during the powered descent phase of the lunar lander, an online guidance algorithm based on sequential convex optimization is proposed. Firstly, based on the lander dynamic model considering the lunar surface curvature and lunar rotation, the model and constraints are convexified to obtain a second order cone programming (SOCP) problem. Then, the classical convex optimization method is improved to estimate and compensate the time varying acceleration profile in real time, which improves the performance of the existing optimization algorithm and enables the lander to land with high precision under the premise of saving fuel as much as possible. The simulation results show that compared with the classical explicit guidance law, the proposed algorithm consumes less fuel in the powered descent phase. The shooting analysis results under various position deviations show that the proposed algorithm can meet the performance requirements. Even if the initial position has a large fluctuation of ±2500 m, it can still complete the powered descent guidance with high precision speed and position.

Key words: Lunar soft landing, Fuel optimal control, Precision landing, Sequential convex optimization, Nonlinear programming

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