Title:
A Controller Development Methodology Incorporating Unsteady, Coupled Aerodynamics and Flight Control Modeling for Atmospheric Entry Vehicles

dc.contributor.advisor Mavris, Dimitri N.
dc.contributor.author Ernst, Zachary J.
dc.contributor.committeeMember Costello, Mark
dc.contributor.committeeMember Sankar, Lakshmi
dc.contributor.committeeMember Robertson, Bradford
dc.contributor.committeeMember Korzun, Ashley
dc.contributor.department Aerospace Engineering
dc.date.accessioned 2023-01-10T16:23:17Z
dc.date.available 2023-01-10T16:23:17Z
dc.date.created 2022-12
dc.date.issued 2022-11-01
dc.date.submitted December 2022
dc.date.updated 2023-01-10T16:23:17Z
dc.description.abstract Atmospheric entry vehicle aerodynamics, flight dynamics, and control mechanisms are inherently coupled and unsteady. The state-of-the-art disciplinary models used for Mars entry vehicle simulation do not directly account for these time-dependent interactions, resulting in increased model fidelity uncertainty that can negatively affect controller performance. This can be especially detrimental given the more rigorous landing precision requirements and increased technological and volitional uncertainty expected for future missions. This work seeks to formulate and implement an entry controller tuning methodology that directly accounts for coupled, unsteady entry vehicle aerodynamic and control system behavior. The methodology uses a 6-degree-of-freedom coupled CFD-rigid body dynamics (RBD) model, extended to include flight control system modeling, for flight simulation while preserving unsteady flow history. This is capable of high-fidelity simulation to evaluate the performance of a controller, but the high cost makes it infeasible to directly use the state-of-the-art methodology for controller tuning which relies on thousands of short-duration simulations. Instead, multifidelity optimization is used. The coupled model is run to evaluate promising designs at high fidelity, while a lower-fidelity model is used to rapidly explore the design space. Crucially, each time the coupled model is executed, it produces new time-accurate trajectory and aerodynamic data that can be added to the training data for the low-fidelity aerodynamic surrogate model. A multifidelity surrogate is then constructed to provide a correction between the low- and high-fidelity results. As tuning proceeds, knowledge of the model is thus gained both by data fusion of the controller performance metrics, and by decreasing aerodynamic error in the low-fidelity surrogate. The methodology was developed through numerical experimentation with an entry vehicle equipped with a single-axis internal moving mass actuator for pitch control. A feed-forward neural network architecture with better performance than a state-of-the-art database was identified for use as the low-fidelity aerodynamic surrogate. A fusion-based multifidelity optimization method is implemented to leverage the quasi-hierarchical nature of the coupled and low-fidelity models. The methodology is demonstrated for tuning an angle of attack controller, yielding a controller that has better performance than one that is tuned using the state-of-the-art methodology.
dc.description.degree Ph.D.
dc.format.mimetype application/pdf
dc.identifier.uri http://hdl.handle.net/1853/70126
dc.language.iso en_US
dc.publisher Georgia Institute of Technology
dc.subject Computational fluid dynamics
dc.subject Rigid body dynamics
dc.subject cfd-rbd
dc.subject 6-degree-of-freedom
dc.subject Mars
dc.subject Entry descent and landing
dc.subject Controller tuning
dc.subject Free-flight simulation
dc.subject Surrogate modeling
dc.subject Multifidelity optimization
dc.title A Controller Development Methodology Incorporating Unsteady, Coupled Aerodynamics and Flight Control Modeling for Atmospheric Entry Vehicles
dc.type Text
dc.type.genre Dissertation
dspace.entity.type Publication
local.contributor.advisor Mavris, Dimitri N.
local.contributor.corporatename College of Engineering
local.contributor.corporatename Daniel Guggenheim School of Aerospace Engineering
local.relation.ispartofseries Doctor of Philosophy with a Major in Aerospace Engineering
relation.isAdvisorOfPublication d355c865-c3df-4bfe-8328-24541ea04f62
relation.isOrgUnitOfPublication 7c022d60-21d5-497c-b552-95e489a06569
relation.isOrgUnitOfPublication a348b767-ea7e-4789-af1f-1f1d5925fb65
relation.isSeriesOfPublication f6a932db-1cde-43b5-bcab-bf573da55ed6
thesis.degree.level Doctoral
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