Navigation, Guidance, Control and Dynamics Commons^™

A Data-Driven Koopman Framework For Station-Keeping On Near Rectilinear Halo Orbit, Anusha Sharma Malladi

Theses and Dissertations

Cislunar missions have gained significant attention in recent decades, motivating the need for efficient modeling and reliable control. In this work a Koopman operator based framework is developed for approximating the error dynamics around a reference Near Rectilinear Halo Orbit (NRHO) in the Earth-Moon Circular Restricted Three-Body Problem (CR3BP). A decoder free neural network is used to learn a lifted linear representation of the nonlinear CR3BP dynamics and a residual based approach is used to identify the corresponding control input matrix. The model is then implemented in a receding-horizon target point controller and compared with uncontrolled propagation and a State …

Machine Learning For Predictive Energy And Emissions Modeling Of Vehicles And Power Grids In The United States, S M Tanvir Faysal Alam Chowdhoury

Dissertations

The environmental benefits of electric vehicle (EV) adoption depend on more than replacing internal combustion engine vehicles with electric powertrains. EV adoption reshapes electricity demand, interacts with regional generation mixes, and influences travel behavior and congestion, creating a coupled transportation-energy system in which vehicle and power-plant emissions must be evaluated together. This dissertation develops machine-learning frameworks for predicting energy consumption and emissions from vehicles and power grids under rising EV adoption. The first component forecasts grid emissions from EV charging. Using simulation data from NREL's Cambium database, a Prophet-based time-series framework predicts carbon dioxide, nitrous oxide, and methane emission rates …

Noise-Optimized Routes For Air Taxi, Waleed Raza

Doctoral Dissertations and Master's Theses

Community noise is a primary barrier to the public acceptance and deployment of Advanced Air Mobility (AAM) and Urban Air Mobility (UAM) air taxi operations. This dissertation develops a coupled siting, routing, and noise optimization framework that links vertiport placement to its downstream acoustic consequences, demonstrated through a Daytona Beach case study. Candidate vertiports are screened and selected using accessibility, safety, demand, and feasibility criteria, and the selected sites form a directed network of 20 routes. Each trajectory is evaluated with a physics-based acoustic pipeline reporting Lmax, SEL, and EPNL at school, hospital, and residential receptors, showing that received exposure …

Optimal Integrated Cfd-Gnc Model For Drag-Based Reentry Dynamics, Sebastian Lopez

Doctoral Dissertations and Master's Theses

This research focuses on optimizing the control of a drag-maneuvering, Starship-class re-entry vehicle by closely integrating high-fidelity aerodynamic data derived from Computational Fluid Dynamics (CFD) simulations, specifically using StarCCM+. The aerodynamic models, tailored to the unique geometry of a drag-maneuvering body, are seamlessly incorporated into a guidance, navigation, and control (GNC) framework. This integration enables closed-loop CFD simulations with real-time control feedback, allowing for direct analysis and optimization of vehicle stability, trajectory, and control demands throughout the re-entry process.

Building upon the work of Gaglio and Bevilacqua, this advanced CFD-GNC model introduces high-order aerodynamic effects, such as aerodynamic moments and …

System Integration And Validation Of The Cal Poly Spacecraft Attitude Dynamics Simulator Mk. Iv, Bricen S. Rigby

Master's Theses

The Cal Poly Spacecraft Attitude Dynamics Simulator (SADS) is an ongoing project that seeks to enable the simulation and validation of sensors, actuators, and control logic related to spacecraft attitude control. The SADS platform rests atop a spher- ical air-bearing device which allows for nearly frictionless rotation in all three axes. The orientation of the platform is controlled by four reaction wheels arranged in a pyramidal configuration. Over the past few years, there have been significant updates to the reaction wheel subsystem, as well as requests for a more capable central com- puter. Therefore, a new system architecture for the …

Development Of A Computer Vision Based Rendezvous And Docking Test Platform, David T. Forbes

Master's Theses

This thesis presents the work completed in the development and testing of a low-cost modular sensor package capable of rendezvous and docking by providing a vehicle with relative navigational commands. These navigational commands are created using relative localization data gathered and processed onboard the sensor package, with validation, in post-processing, against global localization data. This research aims to reduce the cost of smaller autonomous vehicles by removing the need for custom control units, as its modular nature will allow it to be adapted to many different systems and vehicles. Discussed within this thesis is the rapid prototyping, development, and testing …

Development Of A Free-Floating Space Robotic Simulator, Truman: Terrestrial Robotic Unit For Multibody Analysis And Navigation, Jackson W. Cordova

Master's Theses

This work describes the development of a 3 Degree-of-Freedom (DOF) robotic manipulator for use on a free-floating planar air-bearing vehicle. The system developed aims to serve as a foundation for future space robotics research at the California Polytechnic State University (Cal Poly)’s Space Robotics Laboratory. Systems doc- umentation describes conceptual operation and architecture of the proposed system: Terrestrial Robotic Unit for Multibody Analysis and Navigation (TRUMAN). The key operation of TRUMAN is to study a self launch maneuver of a free-floating ve- hicle including 4 distinct phases: launch off a fixed rail, coast, reorientation using manipulator motion, and capture of …

Spaceotter: A Floating Spacecraft Simulator Air Bearing Vehicle For Hardware-In-The-Loop Experiments And Research, Alexander Debartolo

Master's Theses

Growing interest in nanosatellites has increased demand for accessible ground-testing methods, which have historically been expensive and restricted. Floating Spacecraft Simulators (FSS), built around Air Bearing Vehicles (ABVs), address this gap by approximating a zero-gravity, friction-minimized environment suitable for testing spacecraft control systems, robotics, and propulsion on the ground.

This thesis presents the design, realization, and initial performance characterization of the Space Optically Tracked Testbed for Experiments and Research (SpaceOTTER) ABV, developed for the Cal Poly Space Robotics Lab. SpaceOTTER is the first step toward emulating the 3 degree of freedom (3-DOF) planar dynamics of a simulated spacecraft and is …

Hamster: Hybrid-Actuated Mobile Spherical Terrain Exploration Rover, Winnie Gao

Master's Theses

The expansion of space exploration to increasingly challenging planetary environments requires mobility systems capable of extreme traversal capabilities and operational reliability. This thesis presents the design, development, and testing of a low-cost Hybrid-Actuated Mobile Spherical Terrain Exploration Rover (HAMSTER) intended for use on a planetary surface exploration mission. HAMSTER uses a pendulum-based actuation method for steering and an actuated internal shaft to propel the vehicle forward. The internal structure includes a two-tiered central case composed of the navigation control module, accelerometer, motor controller, primary DC motor, battery, voltage regulators, Raspberry Pi, pendulum servo motor, and drive shafts. Additive manufacturing through …

Design And Implementation Of An Embedded Control System For The Cal Poly Spacecraft Attitude Dynamics Simulator, Neil Mahesh Bedagkar

Master's Theses

This thesis presents the development of a cascaded reaction wheel control system for Cal Poly's Spacecraft Attitude Dynamics Simulator. This work considers system architecture, empirical modeling, high-fidelity simulation, embedded firmware, hardware integration, and experimental characterization. In discrete-time simulation, it is shown that nonlinear direct model reference adaptive control (NDMRAC) enables a nonlinear, partially known plant with realistic actuator dynamics to track the response of a canonical second-order transfer function, with settling time within 4.67% and percent overshoot within order of magnitude of the second-order response. In hardware, the feasibility of a cascaded reaction wheel control architecture is experimentally demonstrated, achieving …

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 …

Aircraft Fault Detection Via Weight And Bias Analysis Of A Custom First Neural Network Layer, George Harrison Chen

Theses and Dissertations

Fault detection in aircraft is traditionally handled through redundant hardware and comparison algorithms to detect failures. Alternatives like model-based residual generation and data-driven approaches such as supervised fault classification and unsupervised anomaly detection have been explored, but they suffer from practical limitations; model-based methods require accurate system models, and data-driven methods have large constraints on the data limiting scalability and adaptability. This work presents a purely data-driven neural network architecture featuring a custom first layer designed for real-time fault detection where the weights and biases of this layer are used to detect faults. The network requires zero supervision and complements …

Safe Control Design For Quadruped Locomotion In Unstructured Environments Using Linear Transfer Operators, Sriram Sundar Krishnamoorthy Shankara Narayanan

All Dissertations

Deploying quadruped robots in unstructured, obstacle-rich environments requires control and planning methods that remain safe and reliable despite complex terrain geometry, limited sensing, and inevitable modeling errors. This thesis develops operator-theoretic tools for safe control design of robotic systems using linear transfer operators, with a focus on quadruped locomotion in unstructured environments. The central goal is to develop a unified operator-theoretic framework for safe control design based on the Perron–Frobenius (P–F) and Koopman operators. In particular, the thesis leverages \emph{density functions} to develop safe navigation frameworks in the dual space of densities. In the operator-theoretic perspective, the P–F operator governs …

Adaptive Artificial Potential Field Guidance And Control For Autonomous Docking With Uncooperative And Unknown Spacecraft, Steven Holmberg

Theses and Dissertations

The increasing demand for on-orbit servicing (OOS), active debris removal (ADR), and space domain awareness (SDA) missions has increased the need for autonomous spacecraft rendezvous and proximity operations (RPO) with uncooperative and unknown targets. Traditional guidance and control methods are typically designed for cooperative systems with known geometry and state information. This work builds on previous research to develop and evaluate an artificial potential field (APF)-based control framework capable of autonomous operation with minimal prior target knowledge and applicability to both relatively static and tumbling spacecraft.

The proposed APF formulation incorporates established safety constructs from cooperative docking systems, including an …

Analysis Toolkit For Potential Lunar Landing Zones, Jacobo Matallana

Morehead State Theses and Dissertations

A thesis presented to the faculty of the College of Science and Engineering Morehead State University in partial fulfillment of the requirements for the Degree Master of Science by Jacobo Matallana on April 24, 2026.

Cooperative Unmanned Aerial System (Uas) Geolocation Of Emitters, Christopher Peters

Electrical Engineering Theses and Dissertations

A collection of unmanned aerial systems (UAS) can be networked as a cooperative wireless sensor array to geolocate an unknown-location RF emitter using time-based measurements. In operation, however, environmental multipath and hardware errors in sensor positioning and timing can degrade emitter localization accuracy and limit the practicality of single-snapshot solutions. This dissertation evaluates time-of-arrival and time-difference-of-arrival (TOA/TDOA) geolocation for cooperative UAS arrays under realistic error sources and develops geometry-control strategies that actively reduce localization uncertainty through iterative UAS repositioning.

This work studies the Location on a Conic Axis (LOCA) method for emitter localization. Using Monte Carlo simulations with hardware error …

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 …

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 …

Set-Theoretic Reachability-Informed Model Predictive Control For Mechanical And Aerospace Systems, Jinaykumar Nitinkumar Patel

Mechanical and Aerospace Engineering Dissertations

Modern mechanical and aerospace systems increasingly operate autonomously in environments characterized by nonlinear dynamics, uncertainty, and safety constraints. In these settings, estimation and control methods based on nominal models and single-point trajectory predictions are usually insufficient to ensure safe and reliable operation. This dissertation uses a set-theoretic perspective, in which the system state, uncertainty, and admissible behavior are described by sets instead of point estimates. The key question is not only what the state is, but what set of states remains consistent with the dynamics, disturbances, control limits, and available measurements. This provides bounded descriptions of uncertainty and supports control …

Students For The Exploration And Development Of Space (Seds) Air Brake Subsystem: High-Altitude Autonomous Apogee Modulator System For High-Powered Rockets (Haamshr), Camden J. Maclean, Matthew Wharton, Nick Revis, Colin Guido

Honors Theses and Capstones

The objective of this project was to research, design, fabricate, and analyze an autonomous apogee modulation air brake system for the University of New Hampshire (UNH) Students for Exploration and Development of Space (SEDS) high-powered rocket as competitors in the Friends of Amateur Rocketry – Oxidizers Uninhibited Tournament (FAR-OUT) competition.

This air brake system would be developed with considerations for full autonomy, structural reliability, and repeatable deployment. The design would also be easily integrated into the existing high-powered rocket airframe and mechanically simple to increase reliability and practical functionality. The final design would be evaluated using finite element analysis simulation …

Constrained Dynamics Of Rapid Orbit Motion Emulator (Rome) Using Udwadia-Kalaba Approach, Keanu Brayman

Honors Undergraduate Theses

The Rapid Orbit Motion Emulator (ROME) is designed to be a hardware-in-the-loop (HIL) testbed for orbital control algorithms. It consists of a four-wheeled ground vehicle and a six-degree-of-freedom robotic manipulator. This work investigates the use of optimal control to execute orbital trajectories on ROME using the Udwadia-Kalaba (UK) formulation to model the system dynamics. The UK formulation is a novel method to derive equations of motion for constrained systems. Unlike traditional approaches, the UK approach can be applied directly to any constrained dynamical system. This project utilizes the UK approach to derive dynamics with trajectory following constraints for the ROME …

Autonomous Uav Mission Planning Under Threat Using Model Predictive Control With Proportional-Navigation Pursuers, Mehmet B. Ozcelik

Mechanical and Aerospace Engineering Theses

Autonomous unmanned aerial vehicles (UAVs) operating in contested environments must

complete mission objectives while avoiding restricted regions, radar exposure, and pos-

sible interception. This thesis develops a MATLAB-based simulation framework for

two-dimensional UAV mission planning under threat using model predictive control and

proportional-navigation chasers. The mission requires the UAV to travel from a start

location to a goal while visiting required checkpoints and avoiding no-fly zones and radar

regions. A chaser attempts to intercept the UAV using either a basic pure-pursuit-style

law or a proportional-navigation guidance law.

The framework integrates environment generation, augmented visibility-graph rout-

ing, waypoint management, UAV kinematic …

Llm-Driven Closed-Loop Uav Control With Obstacle-Aware Model Predictive Control, Halimcan Yasar

Mechanical and Aerospace Engineering Theses

This thesis presents a closed-loop control architecture for uncrewed aerial vehicles (UAVs) in which a large language model (LLM) serves as a high-level decision module operating over a persistent, metric 3D world model.

Rather than generating low-level commands or open-loop plans, the LLM selects one parameterized maneuver per decision step from a small, verified library of flight primitives conditioned on a structured representation of the drone state, tracked object positions, and mission specification.

Translational motion is executed by a planar model predictive controller (MPC) with soft obstacle avoidance, using obstacle hypotheses provided by the LLM, so that safety-critical constraint handling …

Active Altitude Control For High Powered Rockets, Henry Allen, Jason Secora, Charles Williams, Donavon Sanchez, Caleb Nedoma

Williams Honors College, Honors Research Projects

The International Rocket Engineering Competition (IREC) is the premier collegiate high power rocketry competition in the world hosted by the Experimental Sounding Rocket Association (ESRA). The Akronauts Rocket Design team has been competing in IREC since 2015 and have won several awards. The main goal of IREC is to launch a rocket to a specified altitude of 10k, 30k, or 45k ft while carrying a payload and successfully recover with little to no damage.

The control of a typical high-powered rocket is purely passive; the center of pressure of the rocket must be behind the center of gravity with respect …

Gaussian Process Regression–Based Uncertainty Quantification For Unmanned Aircraft System Traffic Management And Advanced Air Mobility Applications, Aakarshan Khanal

Mechanical and Aerospace Engineering Dissertations

Uncertainty quantification has gained significant attention in recent years as a research area in dynamical systems. Mathematical representations of the physical system, combined with an understanding of model uncertainties, enable the propagation of uncertainty in temporal space, which allows us to make informed decisions. However, what if the true dynamics of the system is unknown or too complex to define explicitly? In such cases, the system’s behavior can instead be inferred or learned from observed input–output data rather than from an analytical or physics-based model. To this end, this dissertation focuses on developing a data-driven framework for nonparametric dynamics modeling, …

Graph Based Planning With Guarantees, Trazon Tyrik Jimerson

Mechanical Engineering ETDs

This thesis presents two graph-based methods with formal guarantees for motion planning and routing. First, the invariant-set motion planner (ISMP), which uses constraint admissible positive invariant (CAPI) sets of closed-loop dynamics, is adapted for spacecraft attitude planning to avoid moving keep-out zones. Contributions include time bounds for maneuvers via exponential stability, a single-stage reachability graph from one-step backward reachable CAPI sets, and its multi-stage expansion to certify node safety over time. Simulations verify safe attitude control with moving obstacles. Second, we formulate a convex optimization problem over a network for evacuation planning with operational constraints such as helicopter capacity and …

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 …

Development And Test Of An Automatic Mass Balancing System For Cal Poly's Spacecraft Attitude Dynamics Simulator, Cameron B. Zorio

Master's Theses

The Cal Poly Spacecraft Attitude Dynamics Simulator (SADS) is an ongoing project to develop an air-bearing platform capable of recreating on-orbit rotational dynamics with near frictionless and torque-free rotations. However, any offset between the platform's center of rotation and its center of mass will introduce a torque due to gravity.

This thesis presents the design, implementation, and experimental evaluation of a low-cost, automatic mass balancing system for the SADS to address this challenge. A new modular sliding mass system was developed that overcomes issues faced in previous iterations of the SADS, providing real-time positional control of the masses and a …

Understanding Policy Transfer Under Decomposition And Coordination: Sequential Reinforcement Learning With Relaxation-Based Feasibility Control, Aannand Lal

All Theses

This thesis investigates how decomposition and coordination (D&C) choices influence exploration, learning, and transfer in reinforcement learning (RL) based design frameworks. A unified methodology is developed to evaluate generality under decomposition and to demonstrate sequential coordination on a representative physical task. The generality study holds the underlying physics constant while varying problem presentation - specifically scalarization weights, objective orientations, and feasibility handling. A train-evaluate matrix is constructed in which each trained policy is assessed across all alternative decompositions. Set-based diagnostics quantify generality through exact-match identity, Jaccard similarity of distinct feasible states, total feasible coverage, and Pareto-front quality. Results show that …