A Real-Time Algorithm for Non-Convex Powered Descent Guidance

Abstract

The on-board solution of constrained optimal control problems is a key technology for future entry, descent and landing systems. The constraints that must be satisfied to enable advanced navigation routines require powered descent guidance solutions that consider the coupled rotation and translation of the vehicle, leading to a non-convex 6-degree-of-freedom powered descent guidance problem. This paper builds on previous work and refines a successive convexification algorithm to be compatible with common flight code requirements. We highlight the aspects of each algorithmic step that are especially relevant for maximizing the computational performance. A case study is presented using the most general landing problem for which the optimal solution is theoretically known and that contains both rotational and translational states. We demonstrate that the real-time implementation achieves less than 1% sub-optimality with runtimes on the order of 100 ms on a single 3.2 GHz Intel i5 core with 8 GB of RAM. These results suggest that the same design methodology applied to the full 6-degree-of-freedom landing problem is capable of producing fast enough runtimes to be viable for future entry, descent and landing systems.