Space Vehicles Commons^™

Flysurf: A Flying Robotic Surface With Shape Morphing And Motion Control, Kevin Aubert De Luchi Lomellini

Electrical and Computer Engineering ETDs

This thesis introduces FlySurf, a novel flying robotic surface capable of simultaneous shape morphing and motion control. FlySurf is modeled as a mesh-based dynamic structure actuated by multiple unmanned aerial vehicles, enabling complex deformations during flight. The proposed control architecture comprises three main components. First, a state estimator to infer the robotic surface state from limited observations. Second, a shape trajectory planner that incorporates an affine deformation term to preserve surface integrity during shape transitions. Third, a surface controller to minimize the error between the desired and actual surface configurations.

The methodology is validated through realistic simulations and hardware experiments, …

Theory And Algorithms To Learn, Propagate, And Exploit Uncertainty For Stochastic Optimal Control Of Dynamical Systems, Vignesh Sivaramakrishnan

Electrical and Computer Engineering ETDs

Non-Gaussian uncertainty frequently arises in learning and control problems involving stochastic dynamical systems, particularly in autonomous vehicles, UAVs, satellites, and robotics. In this dissertation, we propose a new framework that leverages characteristic functions that provides a frequency-domain representation of random variables. The dissertation is structured into three key areas. First, we address model-based stochastic optimal control for linear systems with non-Gaussian noise, demonstrating that characteristic functions can be used to enforce chance constraints and control systems toward desired distributions. Second, we explore data-driven stochastic control, utilizing empirical characteristic functions to handle systems with unknown disturbances. In addition, we derive several …

Nonlinear Least Squares 3-D Geolocation Solutions Using Time Differences Of Arrival, Michael V. Bredemann

Mathematics & Statistics ETDs

This thesis uses a geometric approach to derive and solve nonlinear least squares minimization problems to geolocate a signal source in three dimensions using time differences of arrival at multiple sensor locations. There is no restriction on the maximum number of sensors used. Residual errors reach the numerical limits of machine precision. Symmetric sensor orientations are found that prevent closed form solutions of source locations lying within the null space. Maximum uncertainties in relative sensor positions and time difference of arrivals, required to locate a source within a maximum specified error, are found from these results. Examples illustrate potential requirements …