Convex Programming Approach of Robust Powered Descent Guidance through Dynamic Tube MPC

Abstract

This paper presents robust powered descent guidance(PDG) algorithm based on dynamic tube model predictive control(MPC). Employing the dynamic tube MPC as a baseline guidance methodology, the modeling error and disturbances are explicitly considered in the MPC problem and the robust control invariant tube geometry is simultaneously optimized along with the original powered descent guidance states. Furthermore, the proposed robust PDG problem is transformed into convex optimization framework through sequential convex programming( SCP) algorithm which is suitable form for real-time application. In the end, numerical experiments are carried out to validate the performance and robustness of the proposed PDG algorithm.