Towards Autonomy: Leveraging Nonlinearity In Predictive And Convex Optimization For Space Vehicle Guidance And Control

As a new age of spaceflight approaches, space vehicle guidance and control methodologies increasingly rely on optimization-based methods, which should be capable of handling complex dynamics, real-world constraints, and limited computational resources. While model predictive control (MPC) and sequential convex programming (SCP) techniques offer promising capabilities, their performance may be restricted when underlying dynamics are over-simplified relative to the true mission environment. This thesis addresses that gap by incorporating nonlinear, mission-specific dynamics in predictive and convex optimization frameworks to improve accuracy, efficiency, and applicability to spacecraft operations. The first part of this work is focused on the development of trajectory optimization techniques that are efficient in both computation time and fuel use. In the cislunar environment, a nonlinear optimization approach combines two-point boundary value problem solutions with an MPC-inspired method, which produces feasible and fuel-efficient trajectories under the three-body dynamics while improving on computational efficiency. This work is further expanded to the formulation of a dual-objective SCP method for far-range spacecraft rendezvous, which enables fuel-optimal solutions that account for disturbances and nonlinear relative motion, offering significant improvements in solve time relative to nonlinear programming methods. The second component focuses on attitude control of a magnetically actuated dual-spin satellite, where MPC policies are constructed that leverage successive linearizations and SCP-inspired predictions to achieve high-precision attitude control under mission-defined constraints. These results demonstrate the optimization-based guidance and control methods benefit substantially from formulations that reflect the nonlinearity of real spacecraft dynamics. When predictive and convex optimization techniques leverage these dynamics, they enable guidance and control solutions that are more accurate, efficient, and better suited for the coming age of autonomous spaceflight.

Author dc:creator

• Halverson, Robert David

• Attitude control
• Nonlinear dynamics
• Predictive control
• Sequential convex programming
• Spacecraft guidance

Language dc:language.iso

en

Handle dc:identifier.uri

https://hdl.handle.net/11299/279240

OAI identifier oai:identifier

oai:conservancy.umn.edu:11299/279240