Navigation, Guidance, Control and Dynamics Commons^™

Health Management And Adaptive Control Of Distributed Spacecraft Systems, Tatiana Alejandra Gutierrez Martinez

Doctoral Dissertations and Master's Theses

As the development of challenging missions like on-orbit construction and collaborative inspection that involve multi-spacecraft systems increases, the requirements needed to improve post-failure safety to maintain the mission performance also increases, especially when operating under uncertain conditions. In particular, space missions that involve Distributed Spacecraft Systems (e.g, inspection, repairing, assembling, or deployment of space assets) are susceptible to failures and threats that are detrimental to the overall mission performance. This research applies a distributed Health Management System that uses a bio-inspired mechanism based on the Artificial Immune System coupled with a Support Vector Machine to obtain an optimized health monitoring …

On-Board Artificial Intelligence For Failure Detection And Safe Trajectory Generation, Eduardo Morillo

Doctoral Dissertations and Master's Theses

The use of autonomous flight vehicles has recently increased due to their versatility and capability of carrying out different type of missions in a wide range of flight conditions. Adequate commanded trajectory generation and modification, as well as high-performance trajectory tracking control laws have been an essential focus of researchers given that integration into the National Air Space (NAS) is becoming a primary need. However, the operational safety of these systems can be easily affected if abnormal flight conditions are present, thereby compromising the nominal bounds of design of the system's flight envelop and trajectory following. This thesis focuses on …

Development And Deployment Of A Dynamic Soaring Capable Uav Using Reinforcement Learning, Jacob Adamski

Doctoral Dissertations and Master's Theses

Dynamic soaring (DS) is a bio-inspired flight maneuver in which energy can be gained by flying through regions of vertical wind gradient such as the wind shear layer. With reinforcement learning (RL), a fixed wing unmanned aerial vehicle (UAV) can be trained to perform DS maneuvers optimally for a variety of wind shear conditions. To accomplish this task, a 6-degreesof- freedom (6DoF) flight simulation environment in MATLAB and Simulink has been developed which is based upon an off-the-shelf unmanned aerobatic glider. A combination of high-fidelity Reynolds-Averaged Navier-Stokes (RANS) computational fluid dynamics (CFD) in ANSYS Fluent and low-fidelity vortex lattice (VLM) …

Optimization Of Rover Wheel Geometries For Planetary Missions, Nikita Amberkar

Doctoral Dissertations and Master's Theses

Rovers have been launched into space for exploration of the Moon and Mars to collect samples of rock and soil. To continue the explorations, the rovers need to have reliable wheels to drive around. However, due to the soil being soft, the wheels on the rover start to lose traction and the wheels sink while driving to various locations. Previous work in this field has been done experimentally or with the use of simulations. Only a few references report the effect of uncertainties in grouser simulation on the traction efficiency. The objective of this work was to (a) Understand the …

Vertical Take-Off And Landing Control Via Dual-Quaternions And Sliding Mode, Joshua Sonderegger

Doctoral Dissertations and Master's Theses

The landing and reusability of space vehicles is one of the driving forces into renewed interest in space utilization. For missions to planetary surfaces, this soft landing has been most commonly accomplished with parachutes. However, in spite of their simplicity, they are susceptible to parachute drift. This parachute drift makes it very difficult to predict where the vehicle will land, especially in a dense and windy atmosphere such as Earth. Instead, recent focus has been put into developing a powered landing through gimbaled thrust. This gimbaled thrust output is dependent on robust path planning and controls algorithms. Being able to …

Controller Design For A Swirl Injection Hybrid Launch Vehicle, Ryan Kinzie

Doctoral Dissertations and Master's Theses

This research is focused on the design of controllers for stabilizing a launch vehicle with an internally originating torque. The motivation for this research arises from the new development of rocket engines which swirl combustion gases to gain combustion stability benefits, and in the case of hybrid rocket engines, fuel regression benefits as well. The stability of the launch vehicle dynamics due to the internal torque has not been discussed before. To the author’s knowledge, this is the first research to address the stabilization problem of the launch vehicle with internal torque. Due to the new design/characteristics of these engines, …

Dynamic Analysis Of Cubesat Impact On Lunar Surface, Dalton C. Korczyk

Doctoral Dissertations and Master's Theses

EagleCam is a pico-satellite (CubeSat) with dimensions of 100 x 100 x 150 mm3 that is going to the moon as a payload of the Intuitive Machines Nova-C lunar lander. The CubeSat’s purpose is to record the lunar landing from a 3rd person view. Unlike other CubeSats, EagleCam is designed to impact the lunar surface and there is no history to build off of. Specifically, EagleCam will need to survive a 30 m drop onto the lunar surface with all internal components fully operational post impact. This thesis is focused on the analytical, numerical, and experimental methods for determining the …

Online Pilot Model Parameter Estimation For Loss-Of-Control Prevention In Aircraft Systems, Frederick Schill

Doctoral Dissertations and Master's Theses

A pilot is a highly nonlinear and incredibly complex controller whose responses are difficult to predict. Many accidents have occurred from pilot error before or after failures and almost always after entering areas of the flight envelope considered as Loss-of-Control regimes. If a pilot's inputs to the flight control system can be predicted, then the introduction of dangerous flight conditions can be readily avoided. Avoidance could take the form of a warning indicator or augmentation of the pilot's inputs. The primary difficulty lies in how to actually predict how the pilot will perform in the future.

Methods to solve this …

Stochastic Model Predictive Control Via Fixed Structure Policies, Elias Wilson

Doctoral Dissertations and Master's Theses

In this work, the model predictive control problem is extended to include not only open-loop control sequences but also state-feedback control laws by directly optimizing parameters of a control policy. Additionally, continuous cost functions are developed to allow training of the control policy in making discrete decisions, which is typically done with model-free learning algorithms. This general control policy encompasses a wide class of functions and allows the optimization to occur both online and offline while adding robustness to unmodelled dynamics and outside disturbances. General formulations regarding nonlinear discrete-time dynamics and abstract cost functions are formed for both deterministic and …