Peter Davis

Date of Award


Document Type


Degree Name

Master of Science in Aeronautical Engineering


Department of Aeronautics and Astronautics

First Advisor

Robert A. Bettinger, PhD


Traditional reentry dynamics and planning has typically explored 3 Degrees-of- Freedom (3 DOF) or pseudo 6-DoF problem formulations. This research expands upon previous work and presents a path-constrained optimal control formulation of a fully 6 Degrees-of-Freedom (3 DOF) dynamic system for an unpowered Reentry Vehicle (RV). In a full 6-DoF dynamic system, the translation, rotation and rotational rates are continually tracked. A system of equations of motion are developed to express the dynamics of the RV in terms of defined states and the RV's physical control detections. A neural-network is used to approximate the aerodynamic database of an exemplary RV. The resulting highly non-linear dynamic system is generalized such that it could be directly adapted to a given reentry body such as Maneuvering Reentry Vehicle (MaRVs) or a Hypersonic Glide Vehicles (HGV) with appropriate inputs. This research lays the foundation for the integration of the real control parameters into mission planning. The newly developed equations of motion are verified against existing work. The system of highly non-linear equations and constraints are used to express an optimal control problem that investigates the minimum time and minimum control trajectories that impact a mission specified terminal conditions. Using GPOPS-II, an optimal control profile for each case is found within the specified conditions. It is also demonstrated that the multi-dimensional aerodynamic database can be approximated by a series of Artificial Neural Networks (ANN) with acceptable error bounds.

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