Atmospheric Density-Compensating Model Predictive Control for the Targeted Reentry of the HyCUBE Spacecraft Using Drag Modulation

Abstract

HyCUBE is a proposed test platform designed to enable access to large volumes of hypersonic aerothermodynamic flight test data at a low cost by collecting measurements during a targeted atmospheric entry from low Earth orbit. Due to its small form factor, it performs the targeted reentry by controlling the atmospheric drag acting on it as opposed to using a propulsion system. Using drag to control the trajectory of a spacecraft is difficult because of the dependence of the drag force on the atmospheric density which is highly variable, uncertain and difficult to predict. This thesis develops a method for estimating the in-flight density of the atmosphere, which is different than the predicted density used in generating the nominal trajectory of the spacecraft. This information is leveraged within a model predictive control strategy to improve tracking performance, reduce control effort and increase robustness to actuator saturation compared to the state-of-the-art approach. A method is also developed to determine whether a spacecraft that has drifted far from the guidance trajectory is physically capable of recovering, or whether a new guidance must be generated. The estimation and control framework is then tested in a Monte Carlo simulation campaign. These simulation efforts demonstrate that the proposed framework is able to stay within 100 km of the guidance trajectory in 98.4% of cases while the remaining cases were pushed away from the guidance by large density errors that could not be physically compensated for by the drag control device. For the successful cases, the proposed framework was able to guide the spacecraft to the desired location at the entry interface altitude with a mean error of 12.1 km, a maximum error of 142 km, and 99.7% of cases below 100 km. All tracking errors were small enough such that the spacecraft could safely target reentry away from populated areas.