Adaptive Convex Optimization Guidance for Lunar Landing

Abstract

In this paper, a novel guidance algorithm based on adaptive convex optimization is proposed to ensure robustness in the uncertainty of a lunar lander’s parameters and satisfy the constraints of terminal position, velocity, attitude, and thrust. To address the problem of parameter uncertainty in the landing process, the parameter-adaptive method is used to achieve online real-time optimal estimations of specific impulse and mass by the optimal observer, and the estimated parameters are used to realize optimal trajectory programming. To overcome the difficulty in constraining the attitude and the thrust level at the final stage in the convex optimization process, a rapid adjustment phase is added to meet the final attitude and thrust constraints; the target-adaptive method is used to adjust the target adaptively at the same time. Therefore, the position and velocity deviations caused by the rapid adjustment phase can be eliminated by the target offset. Finally, the results of numerical experiments demonstrate the effectiveness of the proposed algorithm.

Symmetric projection optimizer: concise and efficient solving engineering problems using the fundamental wave of the Fourier series

“…At this stage, algorithms for solving optimization problems contain two main categories 13 . One is the traditional optimization method based on mathematical formulas 14 – 16 , and the other is the metaheuristic algorithm based on stochastic processes 17 – 19 .…”