Aerospace Engineering Commons^™

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 …

Nozzle Erosion Reconstruction Model For Data Analysis In Rocket Engines And Correlation With Chamber Pressure, Ryan J. Thibaudeau, Stephen A. Whitmore

Mechanical and Aerospace Engineering Student Publications and Presentations

Graphite nozzles remain the dominant choice for small hybrid and solid rocket motors operating on laboratory and university budgets, owing to their low cost, ease of machining, and rapid turnaround during iterative design campaigns. These same programs, however, must contend with the fact that graphite erodes through coupled thermochemical and mechanical mechanisms when exposed to the oxidizing species generated by high-energy propellant combustion, and the resulting throat-area growth fundamentally alters the time histories of chamber pressure, thrust, and delivered specific impulse. This paper presents a nozzle-erosion reconstruction model that extracts the time-resolved throat area from coupled thrust and chamber-pressure measurements …

Robust Real-Time Uav Target Tracking With Onboard Vision-Based Yaw Control, Rylan Malarchick, Jose Castelblanco, Enrique Amaya, Carmen Dimario, Graysen Brinkman, Chirag Kumar, Kiwon Yoon, Sajid Berhane

Beyond: Undergraduate Research Journal

Autonomous tracking of agile unmanned aerial vehicles (UAVs) presents significant challenges for real-time perception and control systems. This work presents AIRHOUND (Autonomous Intelligent Rotorcraft for Hostile Object Unified Navigation and Detection), a UAV platform implementing vision-based yaw tracking through a modular ROS2 software architecture. The system employs YOLOv8 object detection optimized with NVIDIA TensorRT for embedded deployment on an NVIDIA Jetson Orin companion computer. Detected targets are processed through a geometric tracking module that converts pixel coordinates to angular yaw errors using pinhole camera intrinsics, with a proportional controller generating rate-limited yaw commands. These commands are streamed to a PX4 …

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 …

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 …

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 …

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 …

A Machine Learning-Based Apogee Prediction Methodology For Experimental Student Rockets, Price Hamilton Drawdy

Senior Honors Theses

The ability to predict the maximum altitude of a rocket (apogee) in real-time is incredibly useful for collegiate-level competition rockets. This project creates a machine learning-based real-time apogee prediction methodology. Three model types were tested: linear regression, random forest, and a 3-layer multi-layer perceptron (MLP) neural network. These models were trained on a large dataset of simulated flights. All models performed well on simulated test flights, with the linear regression model showing most promise for use on edge compute. More development and real-world testing are necessary to determine how applicable this method is for real-time operation. Nevertheless, this methodology provides …

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 …

The Pid-Based Three Quadcopter Uavs Formation Control Under External Disturbance, Vo Van An, Trinh Luong Mien

Makara Journal of Technology

This paper presents the design and evaluation of a formation control strategy for three quadcopter UAVs, based on a PID controller in a leader–follower structure, under the influence of external disturbances. Each UAV employs a six-degree of-freedom dynamic model and utilises a cascade PID control architecture, in which the inner control loop stabilises the attitude. In contrast, the outer control loop regulates position and maintains the formation. The PID parameters are tuned using the Ziegler–Nichols method to ensure simple implementation and low computational cost. The performance of the control system is evaluated through simulations in the MATLAB environment for two …

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 …

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 …

Statistical Analysis Of Log Transformation Effectiveness In Air Traffic Movement Forecasting During Covid-19 In South Africa, John Lehlaka Masekoameng

Journal of Aviation Technology and Engineering

This study evaluates the effectiveness of log transformation in enhancing multiple regression models used to forecast air traffic movements (ATMs) in South Africa during the COVID-19 pandemic. Using 60 monthly observations from October 2016 to September 2021, the analysis incorporates variables such as revenue, lockdown levels, COVID-19 metrics, exchange rates, gross domestic product, and population. Two models are compared: one using raw ATMs and another with log-transformed ATMs as the dependent variable.

While the untransformed model shows stronger explanatory power (R² = 0.904, adjusted R² = 0.891) compared to the log-transformed model (R² = 0.772, adjusted R² = 0.741), the …

Spline-Based Factor-Graph Optimization With High-Grade Inertial Sensors, Kyle Leland, Clark N. Taylor, David Woodburn, Randal Beard

Faculty Publications

Inertial measurement units (IMUs) are central to global navigation satellite system-based and alternative navigation solutions. This paper combines three lines of research to explore a novel methodology for using inertial sensors: factor graphs, spline-based trajectory estimation, and high-grade inertial sensing. Spline-based factor-graph trajectory estimation is increasingly used in the literature, especially for asynchronous or high-rate sensors. However, prior models neglect the impact of the Earth’s rotation, which is significant for high-grade IMUs. We extend spline-based factor graphs to incorporate accelerometer and gyroscope models that account for the Earth’s rotation. We apply this approach to simulated data from high-grade inertial sensors …

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 …