Now showing items 11-18 of 18
Geofencing for Small Unmanned Aircraft Systems in Complex Low Altitude Airspace
(2019)
As small unmanned aircraft systems (UAS) are utilized in an increasingly wide variety of commercial and civil applications, safety of flight within low altitude airspace can be improved through use of electronic geofence ...
A Mechanized Error Analysis Framework for End-to-End Verification of Numerical Programs
(2023)
The behavior of physical systems is usually modeled by differential equations. For instance, the aerodynamics of airplanes is modeled by the Navier-Stokes equation; problems of optimal control are modeled by the Ricatti ...
Machine Learning Applications in Spacecraft State and Environment Estimation
(2018)
There are some problems in spacecraft systems engineering with highly non-linear characteristics and noise where traditional nonlinear estimation techniques fail to yield accurate results. In this thesis, we consider ...
Selective Evolutionary Generation Systems: Theory and Applications.
(2010)
This dissertation is devoted to the problem of behavior design, which is a generalization of the standard global optimization problem: instead of generating the optimizer, the generalization produces, on the space of ...
Reduced-Complexity Algorithms for Data Assimilation of Large-Scale Systems.
(2008)
Data assimilation is the use of measurement data to improve estimates of the state of dynamical systems using mathematical models. Estimates from models alone are
inherently imperfect due to the presence of unknown inputs ...
Optimal Information-based Classification.
(2011)
Classification is the allocation of an object to an existing category among several based on uncertain measurements. Since information is used to quantify uncertainty, it is natural to consider classification and information ...
Enhancing Physical Modeling with Interpretable Physics-Aware Machine Learning
(2024)
The burgeoning intersection of machine learning (ML) with physics has catalyzed a transformative approach to physical modeling marked by an enhanced capacity for innovation and discovery. Traditional applications of ML in ...
Development and Application of Hypernetworks for Discretization-Independent Surrogate Modeling of Physical Fields
(2024)
High-fidelity models (HFMs) of physical phenomena are frequently expressed using partial differential equations which require expensive and complex numerical methods for solution. This thesis develops discretization ...