Navigation, Guidance, Control and Dynamics Commons^™

Deep-Learning Based Multiple-Model Bayesian Architecture For Spacecraft Fault Estimation, Rocio Jado Puente

Doctoral Dissertations and Master's Theses

This thesis presents recent findings regarding the performance of an intelligent architecture designed for spacecraft fault estimation. The approach incorporates a collection of systematically organized autoencoders within a Bayesian framework, enabling early detection and classification of various spacecraft faults such as reaction-wheel damage, sensor faults, and power system degradation.

To assess the effectiveness of this architecture, a range of performance metrics is employed. Through extensive numerical simulations and in-lab experimental testing utilizing a dedicated spacecraft testbed, the capabilities and accuracy of the proposed intelligent architecture are analyzed. These evaluations provide valuable insights into the architecture's ability to detect and classify …

Verification And Validation Of Robot Manipulator Adaptive Control With Actuator Deficiency, Sebastian Comeaux

Doctoral Dissertations and Master's Theses

This work addresses the joint tracking problem of robotic manipulators with uncertain dynamical parameters and actuator deficiencies, in the form of an uncertain control effectiveness matrix, through adaptive control design, simulation, and experimentation. Specifically, two novel adaptive controller formulations are implemented and tested via simulation and experimentation. The proposed adaptive control formulations are designed to compensate for uncertainties in the dynamical system parameters as well as uncertainties in the control effectiveness matrix that pre-multiplies the control input. The uncertainty compensation of the dynamical parameters is achieved via the use of the desired model compensation–based adaptation, while the uncertainties related to …

Artificial Intelligence-Assisted Inertial Geomagnetic Passive Navigation, Andrei Cuenca

Doctoral Dissertations and Master's Theses

In recent years, the integration of machine learning techniques into navigation systems has garnered significant interest due to their potential to improve estimation accuracy and system robustness. This doctoral dissertation investigates the use of Deep Learning combined with a Rao-Blackwellized Particle Filter for enhancing geomagnetic navigation in airborne simulated missions.

A simulation framework is developed to facilitate the evaluation of the proposed navigation system. This framework includes a detailed aircraft model, a mathematical representation of the Earth's magnetic field, and the incorporation of real-world magnetic field data obtained from online databases. The setup allows an accurate assessment of the performance …

Development Of A Constellation Simulator For A 5g/Iot Mission Planning System, Franco Criscola

Doctoral Dissertations and Master's Theses

The advancement of 5G and Internet-of-Things technologies has presented new challenges for telecommunications providers. One of the challenges is integrating these technologies with present networks. A solution has been found in low-Earth orbit satellite constellations. On one hand, this method increases coverage and reduces costs, but on the other it raises new problems like how to efficiently manage large constellations of spacecraft. This thesis introduces the Constellation Management System, developed in collaboration with i2Cat foundation. This novel tool is composed of two modules: the simulator and the scheduler. The former propagates satellite motion and computes visibility events to various targets …

Online Aircraft System Identification Using A Novel Parameter Informed Reinforcement Learning Method, Nathan Schaff

Doctoral Dissertations and Master's Theses

This thesis presents the development and analysis of a novel method for training reinforcement learning neural networks for online aircraft system identification of multiple similar linear systems, such as all fixed wing aircraft. This approach, termed Parameter Informed Reinforcement Learning (PIRL), dictates that reinforcement learning neural networks should be trained using input and output trajectory/history data as is convention; however, the PIRL method also includes any known and relevant aircraft parameters, such as airspeed, altitude, center of gravity location and/or others. Through this, the PIRL Agent is better suited to identify novel/test-set aircraft.

First, the PIRL method is applied to …

Rigid Body Constrained Motion Optimization And Control On Lie Groups And Their Tangent Bundles, Brennan S. Mccann

Doctoral Dissertations and Master's Theses

Rigid body motion requires formulations where rotational and translational motion are accounted for appropriately. Two Lie groups, the special orthogonal group SO(3) and the space of quaternions H, are commonly used to represent attitude. When considering rigid body pose, that is spacecraft position and attitude, the special Euclidean group SE(3) and the space of dual quaternions DH are frequently utilized. All these groups are Lie groups and Riemannian manifolds, and these identifications have profound implications for dynamics and controls. The trajectory optimization and optimal control problem on Riemannian manifolds presents significant opportunities for theoretical development. Riemannian optimization is an attractive …

An Online Adaptive Machine Learning Framework For Autonomous Fault Detection, Nolan Coulter

Doctoral Dissertations and Master's Theses

The increasing complexity and autonomy of modern systems, particularly in the aerospace industry, demand robust and adaptive fault detection and health management solutions. The development of a data-driven fault detection system that can adapt to varying conditions and system changes is critical to the performance, safety, and reliability of these systems. This dissertation presents a novel fault detection approach based on the integration of the artificial immune system (AIS) paradigm and Online Support Vector Machines (OSVM). Together, these algorithms create the Artificial Immune System augemented Online Support Vector Machine (AISOSVM).

The AISOSVM framework combines the strengths of the AIS and …

Online Estimation Of Unknown Parameters For Flexible Spacecraft, Nicolo Woodward

Doctoral Dissertations and Master's Theses

Attitude controls methods of highly flexible spacecraft have seen increased interest over the last decades thanks to the technological development of flexible solar panels and deploy-ables, which improves the capabilities of small satellites. However, a high-fidelity model of the flexible mode dynamics is hard to obtain in on-ground testing because not all modes of frequencies can be observed, complicating the controller design. Furthermore, plastic deformations due to long periods of storage of stowed flexible components could result in exciting frequencies outside of the designed controller’s bandwidth, leading to an uncontrollable system. This thesis proposes a method to develop a high-fidelity …

Solar Sailing Adaptive Control Using Integral Concurrent Learning For Solar Flux Estimation, Luis Mendoza Zambrano

Doctoral Dissertations and Master's Theses

In the interest of exploiting natural forces for propellant-less spacecraft missions, this thesis proposes an adaptive control strategy to account for unknown parameters in the dynamic modeling of a reflectivity-controlled solar sail spacecraft. A Lyapunov-based control law along with integral concurrent learning is suggested to accomplish and prove global exponential tracking of the estimated parameters and states of interest, without satisfying the common persistence of excitation condition, which in most nonlinear systems cannot be guaranteed a priori. This involves estimating the solar flux or irradiance from the Sun to account for uncertainty and variation over time in this value. To …

Autonomous Space Surveillance For Arbitrary Domains, David Zuehlke

Doctoral Dissertations and Master's Theses

Space is becoming increasingly congested every day and the task of accurately tracking satellites is paramount for the continued safe operation of both manned and unmanned space missions. In addition to new spacecraft launches, satellite break-up events and collisions generate large amounts of orbital debris dramatically increasing the number of orbiting objects with each such event. In order to prevent collisions and protect both life and property in orbit, accurate knowledge of the position of orbiting objects is necessary. Space Domain Awareness (SDA) used interchangeably with Space Situational Awareness (SSA), are the names given to the daunting task of tracking …

Nonlinear Dynamics Analysis And Control Of Space Vehicles With Flexible Structures, Marco Fagetti

Doctoral Dissertations and Master's Theses

Space vehicles that implement hardware such as antennas, solar panels, and other extended appendages necessary for their respective missions must consider the nonlinear rotational and vibrational dynamics of these flexible structures. Formulation and analysis of these flexible structures must account for the rigid-flexible coupling present in the system dynamics for stability analysis and control design. The system model is represented by a flexible appendage attached to a central rigid body, where the flexible appendage is modeled as a cantilevered Euler-Bernoulli beam. Discretization techniques, such as the assumed modes method and the finite element method, are used to model the coupled …

Optical Orbit Tracking And Estimation, Matthew Gillette

Doctoral Dissertations and Master's Theses

Angles-only initial orbit determination methods are currently limited in their use as they require some prior knowledge of where the observed object will be and when it will be there. This research aims to produce a viable method to automate this process so that objects whose trajectories are not saved in a user’s catalog can be observed. A method is devised using a novel approach to satellite recognition in an image. This method is used in addition to Astrometry to determine the right ascension and declination of the object. This information is then used to either obtain the initial conditions …

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) …

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 …

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 …

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, …

Optimal Sizing And Control Of Hybrid Rocket Vehicles, Srija Ryakam

Doctoral Dissertations and Master's Theses

In the present work, a genetic algorithm is used to optimize a hybrid rocket engine in order to minimize the propellant required for a specific mission. In a hybrid rocket engine, the mass flow rate of the oxidizer can be throttled to enhance the performance of the rocket. First, an analysis of the internal ballistics and the ascent trajectory has been carried out for different mass flow rates of the oxidizer as a function of time, for a fixed amount of oxidizer, in order to study the effect of throttling. Two equivalent problems are considered: in the first problem the …

Trajectory Generation For A Multibody Robotic System: Modern Methods Based On Product Of Exponentials, Aryslan Malik

Doctoral Dissertations and Master's Theses

This work presents several trajectory generation algorithms for multibody robotic systems based on the Product of Exponentials (PoE) formulation, also known as screw theory. A PoE formulation is first developed to model the kinematics and dynamics of a multibody robotic manipulator (Sawyer Robot) with 7 revolute joints and an end-effector.

In the first method, an Inverse Kinematics (IK) algorithm based on the Newton-Raphson iterative method is applied to generate constrained joint-space trajectories corresponding to straight-line and curvilinear motions of the end effector in Cartesian space with finite jerk. The second approach describes Constant Screw Axis (CSA) trajectories which are generated …

Envelope Analysis Of Speed-Controlled Evtol Urban Air Mobility Vehicles, David Thompson

Doctoral Dissertations and Master's Theses

There are many vehicles being developed which rely on electrically driven propellers/rotors for both control and propulsion. Based on these vehicles, it is hypothesized that there exists a size limit for speed-controlled propellers/rotors in terms of propeller/rotor diameter. To investigate this, a scaling method was created to allow for a vehicle to be created without being based on a specific mission or passenger/cargo requirement. Relationships were developed to size both the physical vehicle and the weight of the vehicle based on the propeller/rotor diameter. A simulation of a quadcopter was created for the vehicle and scaled with both propeller/rotor diameter …

Design And Flight-Path Simulation Of A Dynamic-Soaring Uav, Gladston Joseph

Doctoral Dissertations and Master's Theses

We address the development of a dynamic-soaring capable unmanned aerial vehicle (UAV) optimized for long-duration flight with no on-board power consumption. The UAV’s aerodynamic properties are captured with the integration of variable fidelity aerodynamic analyses. In addition to this, a 6 degree-of-freedom flight simulation environment is designed to include the effects of atmospheric wind conditions. A simple flight control system aids in the development of the dynamic soaring maneuver. A modular design paradigm is adopted for the aircraft dynamics model, which makes it conducive to use the same environment to simulate other aircraft models. Multiple wind-shear models are synthesized to …

Modeling Of A Hybrid-Electric System And Design Of Control Laws For Hybrid-Electric Urban Air Mobility Power Plants, Sohail Bin Salam Lahaji

Doctoral Dissertations and Master's Theses

Advanced Air Mobility (AAM) is an emerging market and technology in the aerospace industry. These systems are being developed to overcome traffic congestion. The current designs make use of Distributed Electric Propulsion (DEP): either fully electric or hybrid electric. The hybrid engine system consists of two power sources: prime movers, such as turbine engines, and batteries. The hybrid systems offer higher range and endurance compared with the existing fully electric systems. Hybrid-electric power generation systems for AAM have different mission requirements when compared to systems used in automobiles. Therefore, there is a particular need to model hybrid-electric systems and the …

Adaptive And Neural Network-Based Aircraft Tracking Control With Synthetic Jet Actuators, Joshua Teramae

Doctoral Dissertations and Master's Theses

Wing-embedded synthetic jet actuators (SJA) can be used to achieve maneuvering control in aircraft by delivering controllable airflow perturbations near the wing surface. Trajectory tracking control design for aircraft equipped with SJA is particularly challenging, since the controlling actuator itself has an uncertain dynamic model. These challenges necessitate advanced nonlinear control design methods to achieve desirable performance for SJA-based aircraft (e.g., micro air vehicles (MAVs)). In this research, adaptive and neural-network based control methods are investigated, which are specifically designed to compensate for the SJA dynamic model uncertainty and unpredictable operating conditions characters tic of real-world MAV applications. The control …

Adaptive Augmentation Of Non-Minimum Phase Flexible Aerospace Systems, Michael A. Dupuis

Doctoral Dissertations and Master's Theses

This work demonstrates the efficacy of direct adaptive augmentation on a robotic flexible system as an analogue of a large flexible aerospace structure such as a launch vehicle or aircraft. To that end, a robot was constructed as a control system testbed. This robot, named “Penny,” contains the command and data acquisition capabilities necessary to influence and record system state data, including the flex states of its flexible structures. This robot was tested in two configurations, one with a vertically cantilevered flexible beam, and one with a flexible inverted pendulum (a flexible cart-pole system). The physical system was then characterized …

Geomagnetic Aided Dead-Reckoning Navigation, Andrei Cuenca

Doctoral Dissertations and Master's Theses

The dependence of modern navigation methods on global positioning systems has led to developing alternative algorithms for localization, capable of providing reliable and robust estimations. Global position system is commonly used in a vast majority of the world’s devices, and it can supply real time position and velocity information. However, its accuracy can be compromised by external operational effects such as signal availability, cyber-attacks or weather conditions. This thesis investigates an alternative approach to enhance navigation in GPS-denied environments. Particularly, it develops an integrated navigation architecture based on geomagnetic referencing models capable of dead reckoning at GPS denied intervals. A …

Risk Mitigation For Low Latitude Ground-Based Augmentation System (Gbas) Precision Approach Operations, Richard Walter Cole

Doctoral Dissertations and Master's Theses

The ground-based augmentation system (GBAS) is a safety-critical system consisting of the hardware and software that augments the Global Positioning System (GPS) to provide precision approach and landing capability and is one of the navigational cornerstones of the International Civil Aviation Organization's (ICAO) global transition to space-based technologies. In low latitude regions, where the space-based augmentation system (SBAS) cannot provide adequate precision approach service due to large system errors induced by ionospheric delays, GBAS is the best option to provide the primary navigation function for the modernized global air traffic system. The purpose of the study was to identify patterns …

Dynamics And Control Of Higher-Order Nonholonomic Systems, Jaime Rubio HerváS

Doctoral Dissertations and Master's Theses

A theoretical framework is established for the control of higher-order nonholonomic systems, defined as systems that satisfy higher-order nonintegrable constraints. A model for such systems is developed in terms of differential-algebraic equations defined on a higher-order tangent bundle. A number of control-theoretic properties such as nonintegrability, controllability, and stabilizability are presented. Higher-order nonholonomic systems are shown to be strongly accessible and, under certain conditions, small time locally controllable at any equilibrium. There are important examples of higher-order nonholonomic systems that are asymptotically stabilizable via smooth feedback, including space vehicles with multiple slosh modes and Prismatic-Prismatic-Revolute (PPR) robots moving open liquid …