This project aims at developing advanced entry and powered descent guidance technology for precise planetary landing

This $259,661 Project Grant from the National Aeronautics and Space Administration Shared Services Center will fund the development of advanced entry and powered descent guidance technology for precise planetary landing at Purdue University from April 2021 through April 2022.

The project aims to develop a highly implementable onboard optimal guidance approach that optimizes complete entry, powered descent, and landing trajectories in real-time to achieve fuel-optimal and precise landing for human-scale Mars missions. Key activities include developing computationally efficient mission models incorporating both conventional and direct force control maneuvers; designing an online optimization algorithm leveraging advanced computational techniques; and conducting virtual simulation and experimental verification.

The end-to-end onboard optimal mission planning represents the first attempt to solve multiphase guidance problems as an entire mission based on a robust and scalable optimization method. If successful, the technology advancement funded under this award could push the readiness level of fuel-optimal entry and descent guidance algorithms from level 1 to level 3. The funding is provided through the Science Mission Directorate's $43.001 Science grant program, which supports new scientific discoveries through NASA flight programs.

A human- mars mission requires the delivery of a high payload from the entry interface at a hypersonic speed to a preflight-designated surface location at near-zero speed with pinpoint precision. The supersonic retro-propulsion system required to decelerate a human-scale vehicle consumes significant amount of propellant. IT becomes a challenging task to achieve high precision landing while minimizing fuel consumption during the powered descent phase. Moreover the multi-phase operation (entry descent and landing) nonlinear vehicle dynamics and mission constraints make IT even more challenging to generate onboard fuel-optimal guidance maneuvers to accomplish the mission. The goal of this project is to develop a highly implementable guidance approach that optimizes the end-to-end complete entry powered descent and landing (EDL) trajectories in real-time to achieve the fuel-optimal and precise landing. In pursuit of this goal three essential research objectives will be investigated including (1) developing high fidelity and computationally efficient mission models with both conventional bank-angle control and direct-force control maneuvers for entry flight (2) designing a fast converging online optimization algorithm based on advanced computational techniques and (3) conducting virtual simulation and experimental verification which will jointly contribute to the advances of fuel-optimal entry and descent guidance algorithms to enable precise landing. The end-to-end onboard optimal mission planning is the first attempt to solve multiphase guidance problems as an entire mission based on a robust and scalable optimization algorithm. The approach will start with a new modeling paradigm that unifies mathematical representations of both entry and powered descent guidance problems integrating vehicle dynamics in each phase trajectory and operational constraints and landing precision requirements. This unique model will incorporate direct control of aerodynamic forces in entry flight through modulations of angle of attack and sideslip angle to achieve advanced mobility. A three-degree-of-freedom model based on spherical elements will be constructed first and then expanded to a six-degree-of-freedom model based on dual quaternions considering coupled translational and rotational motions. The onboard mission planning scheme aims to optimize the entire EDL trajectory as a whole including designing simultaneously optimal maneuvers in each phase and selecting an ideal initiation of powered descent. To overcome the computational bottleneck in solving large-scale nonconvex optimization problems the optimization algorithm will leverage breakthroughs in matrix decomposition alternating minimization and cutting plane methods to achieve scalability and robust convergence. The proposed modeling and optimization method will be evaluated via monte carlo simulation implementation in an experimental testbed and final assessment in NASA flight simulations. All these efforts will eventually push the technology from the starting TRL 1 to TRL 3 at the end of the project.