Navigation, Guidance, Control and Dynamics Commons^™

Adaptive Control Combined With Integral Concurrent Learning For Trajectory Tracking Near Asteroids, Alvaro Diaz Rodrigo

Doctoral Dissertations and Master's Theses

Close-proximity operations in the vicinity of Near-Earth Asteroids (NEAs) are essential for scientific studies and possible future planetary-defense missions. Unlike motion around large celestial bodies, spacecraft dynamics near small, rotating asteroids are dominated by weak, highly irregular gravity fields. While full characterization of an asteroid’s shape enables high-fidelity gravitational modeling, such information is typically unavailable in realistic mission scenarios, and in-situ exploration is often required. As a result, the forces acting on the spacecraft cannot be modeled accurately in advance, leading to significant uncertainty in the equations of motion and challenging guidance and control strategies. To address these challenges, the …

Intelligent Flight Control Systems Using Adaptive Deep Neural Networks And Concurrent Learning-Based Design Methods, Maddox C. Morrison

Doctoral Dissertations and Master's Theses

This thesis investigates deep neural network (DNN)-based adaptive control strategies for unmanned aerial vehicles (UAVs) operating under aerodynamic uncertainty and complex actuator dynamics.

The first contribution presents a control strategy employing a concurrent learning (CL)-based DNN training algorithm, which combines online adaptive DNN weight adaptation with offline batch-like training updates using a recorded data stack. The analysis focuses on the closed-loop performance improvements resulting from the use of optimum CL data-selection algorithms, which ensure that the recorded data stack maintains sufficient data diversity to provide a statistically meaningful representation of the operating conditions using a reduced data set. Specifically, this …

Safety-Aware Trajectory Generation For Increased Autonomy In Advanced Air Mobility, Edison Alberto Martinez Samaniego

Doctoral Dissertations and Master's Theses

Advanced Air Mobility (AAM) envisions highly automated aircraft that will enable short and medium range transportation. Unlike conventional aviation, these vehicles are expected to operate closer to populated areas and with increased levels of autonomy, making safe operation under abnormal or degraded conditions a critical requirement. Failures or performance degradation can reduce the maneuvering capability of an aircraft, causing trajectories planned under nominal conditions to become dynamically unfeasible.

This thesis presents a trajectory generation and replanning framework designed to maintain safe and feasible flight under reduced flight envelope conditions for a lift+cruise eVTOL aircraft. A unified control architecture based on …

Reinforcement Learning - Driven Satellite Attitude Recovery: Unknown Faults, Simulation-To-Processor In Loop, Chinmay Mirji, Saeed A Ahmadi

Student Research Symposium (SRS)

Conventional attitude control algorithms often degrade when faced with actuator faults, sensor noise, or system uncertainties. This work presents a reinforcement-learning (RL) framework for satellite attitude recovery under unknown failures, focusing on real-time deployment through a processor-in-the-loop (PIL) setup. A continuous-control DDPG agent is trained in a high-fidelity Python/Basilisk simulation environment, where domain randomization captures variations in inertia, external torque, and actuator limitations to promote robust policy learning.

Evaluating Runtime Monitoring For Reinforcement Learning-Based Flight Control, Andrew Zubyk

Doctoral Dissertations and Master's Theses

Ensuring safety in adaptive flight controls systems is an ongoing challenge in aviation, especially as advancements in artificial intelligence and machine learning (AI/ML) trend upwards. Reinforcement learning is becoming more common in aerospace applications due to the ability to improve these models through training.  While models such as reinforcement learning enable controllers to learn complex behaviors from interaction with the environment, their unpredictability in novel or disturbed conditions raises severe concerns in safety-critical domains. This research investigates the integration of runtime monitoring, a real-time assurance technique, with reinforcement learning-based flight controllers to ensure safety and reliability during flight. By supervising …

Initial Development Of Cooperative Aerial And Ground Vehicles Experimental Testbed, Javier S. Robinson, Morad Nazari

Beyond: Undergraduate Research Journal

Heterogeneous multi-agent systems represents a growing area of research in autonomous vehicles, which involves the real-time cooperation of vehicles operating under different roles or dynamical mod- els. While there is plenty of theoretical work, the existing experimental research focuses on cooperation between physically identical vehicles. This is likely because testing heterogeneous vehicles naturally in- volves more complicated dynamics and communication frameworks to ensure compatibility. The goal of the Cooperative Aerial and Ground Vehicles Experimental (CAGE) testbed is to develop an experimen- tal testbed that involves cooperation of two distinct vehicle models: multiple Crazyflie 2.1 quadcopter drones and at least one …

Parameter Informed Reinforcement Learning For Vehicle System Identification, Nathan Schaff

Doctoral Dissertations and Master's Theses

Accurate system identification is essential for modeling and controlling vehicle dynamics. This dissertation explores the application of Parameter Informed Reinforcement Learning (PIRL) as a novel approach to system identification (SYSID). PIRL integrates prior system knowledge, such as physical parameters, into reinforcement learning (RL) frameworks to improve estimation accuracy. The study begins with an overview of traditional SYSID methods and then introduces PIRL as a modification of standard RL. The research applies PIRL to short-period aircraft dynamics, demonstrating its effectiveness in both offline and online learning frameworks. The dissertation then further explores PIRL’s utility in an indirect model reference adaptive control …

Insights On Ai-Supported Uncrewed And Autonomous Systems Education, Brent A. Terwilliger Ph. D, John Faraca

Publications

Artificial Intelligence (AI) related technology is reshaping the educational experience in programs focused on uncrewed and autonomous systems, aviation, robotics, and aerospace, with growing implications for workforce readiness and cross-sector innovation. Early survey data, capturing student, educator, and employer perspectives, reveals that AI-supported tools are notably changing student engagement, communication, and skills development. Initial indications underscores the importance of AI proficiency and technological familiarity in hiring and workforce development, particularly in technical and operational roles. Key areas of focus include the use of AI to strengthen outreach and interactivity; enrich instruction through intelligent simulations; inform curricular improvements using data analytics; …

Autonomous Landing Of An Unmanned Aerial Vehicle On An Unmanned Surface Vessel Using Model Predictive Control With An Adaptive-Covariance Extended Kalman Filter, Jorge Estupinan

Doctoral Dissertations and Master's Theses

This thesis presents the development of vision-based estimation and model predictive control (MPC) strategies to enable an Unmanned Aerial Vehicle (UAV) to land autonomously on an Unmanned Surface Vessel (USV) subjected to wave-induced motion. An innovative Adaptive-Covariance Extended Kalman Filter (AEKF) implementation was developed for the estimation of the 6 degree-of-freedom USV states using GPS and vision-based measurements of AprilTag markers on the USV landing platform. The AEKF employs an uncontrolled 6 degree-of-freedom nonlinear model augmented with second-order harmonic wave-induced motion dynamics. The AEKF implements two correction techniques: an adaptive covariance adjustment and an artificial covariance inflation regulated by a …

Unresolved Image Simulation For Space Situational Awareness Applications, Fox Coniglario

Doctoral Dissertations and Master's Theses

The knowledge of what lies in orbit around Earth is at best a guess. Decades of spaceflight, debris buildup, and vehicle collisions have contributed to a large number of objects that are simply not able to be catalogued. Ongoing efforts to catalog debris in orbit have reached limits by conventional measures and as such, research is active in the field of in-orbit space situational awareness. This thesis intends to help fill a hole in the development of such orbital platforms by assisting the development of image processing software pipelines though the simulation of unresolved space imagery. The simulation uses accurate …

Adaptive Control For Spacecraft With Flexible Appendages With Unknown Parameters, Nicolo Woodward

Doctoral Dissertations and Master's Theses

Flexible spacecraft pose several challenges in control design due to the uncertain dynamical model and the underactuated nature of these systems. Adaptive and robust controllers are the common choice for these systems to either meet operational requirements like attitude pointing or to suppress vibrations. However, these controllers add complexity in the design of onboard Attitude Determination and Control Systems (ADCS) and the Reaction Control Systems (RCS) for spacecraft maneuvering. The objective of this research is to control a system that undergoes unpredictable and unknown disturbances through onboard derivation of an equivalent reduced order model designed around mounted sensors. The proposed …

Orbital Maneuvers And Interplanetary Trajectory Design Via Reinforcement Learning, Roberto Cuéllar Rangel

Doctoral Dissertations and Master's Theses

This dissertation investigates the application of reinforcement learning (RL) to the design and optimization of low-thrust spacecraft trajectories, with an emphasis on autonomy, adaptability, and robustness in the presence of system uncertainties and unmodeled perturbations. Classical approaches to low-thrust trajectory design are predominantly grounded in optimal control theory, which relies on the availability of precise dynamical models and often requires problem-specific reformulation and solver tuning. While optimal control methods offer high accuracy under deterministic conditions, their sensitivity to stochastic disturbances and computational limitations in highly nonlinear or uncertain environments pose significant challenges for future autonomous space missions.

To address these …

Robust Adaptive Rigid Body State And Mass Property Estimation Via Unscented Kalman Filter On Tse(3) With Process Noise Estimation, Herman Gunter

Doctoral Dissertations and Master's Theses

Mass property estimation, including mass, center of mass, and moment of inertia, is a crucial yet challenging problem in spacecraft autonomy and astrodynamics. Knowledge of mass properties of a spacecraft is essential for future astronautical missions, as changes in the mass properties of a spacecraft due to a shift in cargo distribution often require a careful and costly recalculation to ensure applied control inputs produce the desired results. As spacecraft missions grow in both duration and number, meeting the need for precise and accurate measurements becomes increasingly complex. Stochastic effects, such as angle and velocity random walks, along with persistent …

Experimental Analysis Of Satellite Operator Training Using Game-Based Virtual Reality Simulation, Lana Laskey

Doctoral Dissertations and Master's Theses

Satellite data plays a vital role in modern global infrastructure by enabling communications, navigation, and weather forecasting. As demand for satellite technology grows, so does the need for highly trained satellite ground operators. Traditional training regimens for satellite operators employ simulation using two-dimensional computer console displays paired with the varied ability of trainees to generate abstract mental imagery of the scenario. However, this development of mental imagery imposes a considerable learning curve and cognitive workload on the trainee, which may negatively impact the user experience and knowledge gained during the training scenario.

This experimental study investigated the effects of game-based …

Solar Sailing Adaptive Control Around The Earth-Moon Lagrange Point L4 For Stellar Observations, Luis Mendoza Zambrano

Doctoral Dissertations and Master's Theses

To expand our knowledge about the influence of the Sun in the cislunar region, as well as our understanding of shocks due to Coronal Mass Ejections and large coronal magnetic reconnection, a solar sailing approach is proposed to separately capture lunar occultations and observe the solar corona from L₄ of the Earth-Moon system. Single and multiple shooting techniques are described along with a pseudo arc-length continuation method for preliminary orbit design. Periodic orbits in the vicinity of L₄ are obtained in the context of the Earth-Moon circular restricted three-body problem (CR3BP) and the Sun-Earth-Moon bi-circular restricted four-body problem …

Satellite Reorientation Using Reinforcement Learning Under Unknown Attitude Failure, Matthew Willoughby

Doctoral Dissertations and Master's Theses

This study presents a reinforcement learning (RL) approach for reestablishing communication with deep-space satellites under unknown attitude determination and control system (ADCS) failures. When traditional fault-tolerant control methods cannot restore signal, the proposed RL controller acts as a last-resort measure by autonomously reorienting the satellite’s antenna toward Earth while charging the battery via solar panels. A generic reward function, designed for the RL-based method, enables the controller to adapt to diverse failure scenarios, including severe actuator noise, misalignment, and complete actuator failure. Simulations are conducted in the Basilisk environment and trained with the tonic framework and demonstrate ranging capabilities of …

Utilizing Augmented Reality For Immersive Space Mission Design, Joseph Anderson

Doctoral Dissertations and Master's Theses

Designing spacecraft mission trajectories is a complex, tedious, and stringent process that requires a strong background in astrodynamics and programming due to the complex dynamical environment of space. The current 2D visualization methods for displaying these geometrically abstract trajectories make it difficult to understand the true nature of more complex orbits. Advancements in immersive headsets and their intuitive interaction capabilities make them ideal for solving and understanding 3D problems that require complex spatial representations, revealing an innovative and unique opportunity for the astrodynamics and space mission planning field. This effort covers the development of an immersive space mission design tool …

Adaptive Control Of Thrusters To Account For Deficiencies In Actuator Effectiveness And Model Uncertainties, Matthew Stanko

Doctoral Dissertations and Master's Theses

Future space missions are expected to become ever more ambitious and challenging. A successful mission requires advanced and resilient control algorithms that enable missions, such as satellite refueling, on-orbit inspection, and end-of-life servicing. This thesis explores the development and application of robust and adaptive control laws for an over-actuated spacecraft system with 3 degrees of freedom (DoF) to mitigate the effects of actuator deficiencies and system uncertainties. Additionally, the nature of the system being over-actuated allows for particular actuator degradation and failure. For stability and command tracking, a novel controller is designed and augmented with sliding mode control, adaptive control, …

Coupled Dynamics In The Cislunar Region And Spacecraft Attitude Prediction In A Higher-Fidelity Model​, Annika Anderson

Doctoral Dissertations and Master's Theses

The cislunar region of space is a complex, multi-body dynamical environment that cannot be modeled trivially. Traditional point-mass assumptions made to simplify the mission design process may be insufficient for accurately predicting spacecraft motion in environments where orbit-attitude coupling is non-negligible. One of the most famous of such models is the circular restricted three-body problem. This thesis advances the state of the art in astrodynamics by modeling all bodies in the problem as rigid bodies, allowing for spacecraft orientation to be propagated and considered. Two models are under consideration—the circular restricted full three-body problem (CRF3BP) and a full higher-fidelity ephemeris …

Machine Learning Methods For Hypervelocity Fragment Flyout Characterization, Katharine Larsen

Doctoral Dissertations and Master's Theses

Resulting from breakup events, such as collisions and explosions, hypervelocity fragments create potential hazards for both terrestrial and on-orbit environments, such as terrestrial weapons explosions and satellite breakup events, respectively. To avoid unnecessary damage, an accurate understanding or characterization of hypervelocity fragmentation events is vital. Currently, publicly available two-line elements collected from on-orbit breakup events are limited, excluding pre-detonation parent body conditions, such as orientation, and information of smaller fragments. The uncertainty of these datasets varies between each collected set. Therefore, the overall goal of this work is to employ machine learning to estimate distribution characteristics of a space debris …

Stability Limits Of Uncertain Systems In The Presence Of Unmatched Coupled Dynamics And Actuator Dynamics With Adaptive Architectures, Bronson Saulo

Doctoral Dissertations and Master's Theses

Uncertain systems with coupled dynamics and actuator dynamics are prevalent in various applications spanning private, commercial, and government sectors. While stabilization and command tracking strategies exist, they often rely on idealized assumptions, such as negligible actuator bandwidth limitations and matched coupled dynamics. In order to mitigate actuator-induced limitations, we first employ standard model reference adaptive control (MRAC) architectures. We then proposed two architectures: modified hedging reference modeled based MRAC and modified expanded reference model based MRAC. In order to deal with coupled dynamics, we used an observer design to estimate the states of unmatched coupled dynamics. In addition, Lyapunov stability …

Dual Quaternions For Gravity Recovery Missions, Ryan Kinzie

Doctoral Dissertations and Master's Theses

A dual quaternion-based modeling, state estimation and control approach is introduced as a better alternative to the traditional methods which are currently utilized for gravity recovery missions. The proposed modeling and control approach was verified against and compared to the tangent bundle to Special Euclidean Group 3 through MATLAB simulations. The dual quaternion-based approach shows superior performance over traditional linearized and uncoupled methodologies, in both modeling accuracy of spacecraft translational position, and the ability to control the pose of a test mass relative to its host spacecraft. Utilizing data products from the Gravity Recovery and Climate Experiment Follow-On mission, a …

Modeling The Dynamics Of Flexible Aerospace Vehicles Using The Theory Of Functional Connections, Carlo Lombardi

Doctoral Dissertations and Master's Theses

Modeling and control of flexible vehicles is a topic of high interest in the aerospace field and a key challenge lies in finding accurate mathematical representations of the flexible dynamics of continuous elastic structures that allow simple integration into estimation and control algorithms. The answer was found in approximating the dynamics of these systems with sets of coupled Ordinary Differential Equations (ODE) for which a well-established estimation and control theory is available. Each of the techniques employed to achieve this goal is characterized by its own strengths and limitations. Hence, the main objective of this research is to develop the …

Robust Spacecraft Autonomy For Deep Space Exploration In Special Euclidean Group Se(3), Matthew Wittal

Doctoral Dissertations and Master's Theses

Over the past half-century, humanity has gained extensive experience conducting manned spaceflight near Earth. Arguably, "near Earth" could even include the Moon — the most distant destination humans have reached. However, "near" in this work primarily refers low Earth orbit (LEO). One could argue that we have not truly left Earth since the Apollo, as spacecraft in some LEOs remain subject to atmospheric drag thus emphasizing their continued connection to Earth's immediate environment. Reflecting on this, it becomes clear that humanity has largely remained bound to Earth’s immediate vicinity since the Apollo missions reached the Moon. However, that is set …

An Operational Field Study: A Comparison Of Piloting Uncrewed Underwater Vehicles And Uncrewed Aircraft Systems, David Thirtyacre, Joseph Cerreta, Pete Miller, Kimberly Luthi, Jolee Thirtyacre

Publications

and operations, the ability to cross-train personnel in both Uncrewed Underwater Vehicles and Small Uncrewed Aircraft System operations has become a focal point for efficiency and workforce optimization. This study presents a comparative analysis of the operational and human factor considerations involved in piloting mini UUV and sUASs, highlighting the key similarities and differences in control methods, environmental influences, navigation, emergency procedures, and situational awareness. A qualitative experimental field study was conducted between July 2024 and October 2024, involving real-world deployments of both systems in maritime and aerial environments. Findings indicated that while UUV and sUAS operators relied on remote …

Investigation Of A Busemann Intake At Negative Angle Of Attack, Mark E. Noftz, Andrew N. Bustard, Nicholas J. Bisek, Thomas J. Juliano, Joseph S. Jewell

Publications

A high-speed, shape-transitioned, inward-turning intake was tested in Purdue’s Boeing/AFOSR Mach 6 Quiet Tunnel. The inlet model, called the Indiana Inlet (INlet), had a total contraction ratio of 4.68:1 and a design point of Mach 6 at 0° angle of attack. The model was outfitted with a suite of high-frequency pressure transducers, and the external flowfield was imaged with high-speed schlieren photography. The INlet was tested under low freestream disturbance levels for a variety of freestream unit Reynolds numbers and at-4° angle of attack. An unsteady shockwave near the leading edge of the inlet forebody, indicative of boundary layer separation, …

Model Predictive Control For Autonomous Landing In Complex Scenarios, Konstantinos Sotirakos

Doctoral Dissertations and Master's Theses

The autonomous flight industry is ever-expanding and continuing to push the boundaries of what is possible within the limitations of technology. Multiple companies are exploring the use of autonomous flight for intra-city travel with air taxi services and package delivery vehicles. Other companies are exploring the use of autonomous vehicles for military applications, such as Sikorsky with a next generation Black Hawk helicopter to ensure the safety of soldiers in high threat or altogether dangerous scenarios. In this thesis model predictive control (MPC) algorithms are developed to enable a quadcopter to operate and land autonomously in challenging environments. Specifically, MPC …

Adaptive Control And Estimation Of The Center Of Mass Of A 5-Degree-Of-Freedom Spacecraft Testbed, Pol Fontdegloria Balaguer

Doctoral Dissertations and Master's Theses

In space applications, on-ground experimentation is an essential step in control algorithm validation before real mission application. However, on-ground conditions greatly differ from space ones, where satellites operate under extremely low gravity and friction conditions. A common way to simulate these conditions is with air-bearing-based testbeds. These testbeds reduce friction significantly to almost space-like conditions. Air-bearing technology can provide virtually frictionless translational and rotational motion. However, when frictionless rotational motion is achieved, the testbed becomes highly sensible gravity torque. This external torque is produced by the offset between the predetermined geometrical center of rotation (CoR) and the center …

Assessing The Impact Of Spacecraft Fragmentation In The Cislunar Region, Marta Lopez Castro

Doctoral Dissertations and Master's Theses

In the last decades, space missions have followed great advancements due to technological improvements and the extensive research developed in the field. Some of these missions are increasingly focusing on satellites orbiting the Moon. The Cislunar region is known to have a higher non-linear chaotic component in the dynamics compared to the low-Earth environment. This research is focused on studying the impact that a satellite explosion has in the Cislunar vicinity. The study is conducted for different periodic orbits that are key destinations for Cislunar traffic. By varying the initial conditions, simulations of explosions at different locations of the orbits …

Sliding Mode Control With Chattering Reduction, Suryamshu Ramesh

Doctoral Dissertations and Master's Theses

Sliding Mode Control is a powerful nonlinear control methodology that can handle parametric uncertainties and external disturbances. However, the discontinuous and high-frequency switching nature of the control law introduces the chattering phenomenon, which leads to potential actuator degradation, alterations to the desired response characteristics and, sometimes, instability during control implementation. The main objective of this thesis is to study Sliding Mode Control with chattering reduction. The Sliding Mode Control law involves an equivalent control component and a discontinuous control component. A disturbance estimation is performed based on Lyapunov analysis and adaptive control techniques and then included in the control law …