Parameter-adaptive Convex Optimization for Lunar Landing Trajectory Planning

A parametric adaptive convex optimization lunar landing trajectory planning algorithm based on the optimal observer is proposed for the lunar surface descent landing problem with high accuracy. Firstly，to address the need of minimizing fuel consumption in the main deceleration section of the descent landing，the lunar surface descent landing problem is transformed into a second-order cone planning problem by considering the constraints and the nonconvexity of the dynamical model using a lossless convexification technique；secondly，an optimal observer based on the Riccati equation is designed to reduce the influence of the uncertainty of parameters such as mass and specific impulse during the descent landing process；then the optimal trajectory generated according to the nominal parametric convex The optimal trajectory generated by the optimization is then flown，and the online real-time estimation of the lander parameters is achieved by using the real-time accelerometer measurement information in the process，combined with the thruster output information；after the convergence of the parameter estimation is achieved，the online planning of the optimal trajectory is realized by solving the second-order cone planning problem online. The simulation results show that the observer can achieve online parameter estimation in real time；the algorithm only needs the engine to have a discrete thrust domain compared with other fixed-point landing algorithms，and has the advantage of higher accuracy. © 2023 China Spaceflight Society. All rights reserved.