Navigation, Guidance, Control and Dynamics Commons^™

Physics-Informed Neural Network Based Aerodynamic Modeling Framework, Nathaniel E. Michek

Graduate Theses, Dissertations, and Problem Reports (ETD)

Significant advances have been made in developing aerodynamic models over the years. While these advances span many modeling techniques and data collection methods, certain aerodynamic regimes still pose significant challenges. These regimes commonly occur when an aerodynamic body is under extreme flight conditions. Many of these conditions occur simultaneously in the rare and poorly understood case of a tumbling aerodynamic body. The flight of a tumbling aerodynamic body goes through the entire range of aerodynamic angles, alpha and beta, causing significant non-linearities and time-dependent effects associated with flow separation. During tumbling, the aerodynamic body simultaneously rotates about all three axes …

Evaluation Of Small Unmanned Tailsitter Hybrid Air Vehicles Via Full Flight Simulation, Andrew Spencer Winters

Graduate Theses, Dissertations, and Problem Reports (ETD)

Small Unmanned Aerial Vehicles have exploded in popularity in the past 15 years among researchers and for industrial uses such as agriculture, search and rescue, and infrastructure inspection. Fixed wing and multirotor designs present two major paths that can be taken with these technologies. Fixed wing platforms have superior aerodynamic efficiency but require large areas for takeoff/landing and cannot hold a constant position in space, limiting their use. Multirotor configurations offer a more versatile platform that can maneuver in 3 dimensions independently but lack the endurance of fixed wing vehicles. This thesis analyses a quadrotor biplane and a variable wingspan …

Parameter Estimation Of A 100 Seater Simulated Passenger Aircraft, Michael James Winston

Graduate Theses, Dissertations, and Problem Reports (ETD)

Virtual flight test aircraft provide good opportunities to test new parameter estimation methods. However, good estimates for the parameters in VIRTTAC Castor, a virtual test aircraft, are unavailable. This thesis uses two well-established time domain methods, the Output Error Method and the Filter Error Method, to estimate the parameters of VIRTTAC Castor. Three standard maneuvers were used: Elevator 3-2-1-1, Rudder Doublet, and Aileron Multi-Step. The parameters were estimated across three different flight conditions: weight, altitude and air speed, which resulted in 27 tests for each maneuver. All parameters, and standard deviations estimated are included in the appendix as a table.

End-To-End Neural Network Based Optimal Control For Asymmetric Quadrotor Uas, Ross O'Hara

Graduate Theses, Dissertations, and Problem Reports (ETD)

This thesis presents the development and evaluation of a neural network-based optimal controller for asymmetrically loaded quadrotor unmanned aerial systems (UAS). Traditional control strategies such as PID are typically designed under symmetry assumptions and often degrade in performance when faced with significant loading asymmetries. To address this, a six-degree-of-freedom quadrotor model incorporating rotor dynamics and center-of-mass offsets was developed. A trajectory optimization framework using MATLAB’s fmincon solver generated over 50,000 energy-optimal trajectories across symmetric and asymmetric conditions. These were used to train a range of feedforward neural network architectures in a full-factorial study.

The best-performing controller was identified, having five …

Theory And Algorithms To Learn, Propagate, And Exploit Uncertainty For Stochastic Optimal Control Of Dynamical Systems, Vignesh Sivaramakrishnan

Electrical and Computer Engineering ETDs

Non-Gaussian uncertainty frequently arises in learning and control problems involving stochastic dynamical systems, particularly in autonomous vehicles, UAVs, satellites, and robotics. In this dissertation, we propose a new framework that leverages characteristic functions that provides a frequency-domain representation of random variables. The dissertation is structured into three key areas. First, we address model-based stochastic optimal control for linear systems with non-Gaussian noise, demonstrating that characteristic functions can be used to enforce chance constraints and control systems toward desired distributions. Second, we explore data-driven stochastic control, utilizing empirical characteristic functions to handle systems with unknown disturbances. In addition, we derive several …

Machine Visual Perception From Sim-To-Real Transfer Learning For Autonomous Docking Maneuvers, Derek Worth, Jeffrey Choate, Ryan M. Raettig, Scott L. Nykl, Clark N. Taylor

Faculty Publications

This paper presents a comprehensive approach to enhancing autonomous docking maneuvers through machine visual perception and sim-to-real transfer learning. By leveraging relative vectoring techniques, we aim to replicate the human ability to execute precise docking operations. Our study focuses on autonomous aerial refueling as a use case, demonstrating significant advancements in relative navigation and object detection. We introduce a novel method for aligning digital twins using fiducial targets and motion capture data, which facilitates accurate pose estimation from real-world imagery. Additionally, we develop cost-efficient annotation automation techniques for generating high-quality You Only Look Once training data. Experimental results indicate that …

An Investigation Into The Use Of Amateur Astronomy Equipment For Optical Orbit Determination Using A Mobile Telescope Platform, Johan C. Govaars

Master's Theses

The process of optical orbit determination has long been in the domain of large organizations and stationary observatories with highly specialized scientific equipment. This thesis seeks to determine not only if satellites can be captured regularly using purely commercial-off-the-shelf (COTS) equipment, but also if initial orbit determinations can be made using that data. Moreover, the use of a mobile telescope platform allows users to circumvent the restrictions of fixed observatories such as low horizon viewing restrictions or existing light pollution.

A completely COTS setup was utilized that included an 8-inch Celestron NextStar 8SE telescope with an f/6.3 focal reducer and …

Learning-Based Feature Identification For Rendezvous And Capture Of Non-Cooperative Space Objects, Trupti Mahendrakar

Theses and Dissertations

In recent years, On-Orbit Servicing (OOS) and Active Debris Removal (ADR) have attracted increasing interest due to growing concerns about space debris. This debris poses a significant risk to spacecraft, as collisions can catastrophically end missions and potentially trigger a cascading chain reaction of more debris. Space debris ranges from tiny paint chips to large non-functional spacecraft and even launch vehicle components. One way to mitigate the formation of additional space debris is to reduce the total number of large non-cooperative resident space objects present in operational orbits. This can be achieved through two approaches: de-orbiting these objects as part …

Improving Robustness Of Learning-Based Approaches In Autonomous Systems And Engineering Education, Godwyll Aikins

Theses and Dissertations

This dissertation advances the development of robust learning-based approaches across two complementary domains: engineering education and autonomous systems. Through four studies, this research addresses critical challenges in preparing data-proficient engineers and developing reliable autonomous systems that can operate under uncertainty and incomplete information. The engineering education study examines how mechanical and aerospace engineering undergraduates conceptualize and develop data proficiency skills essential for modern engineering practice. Through interviews with 27 students, the research employs the How People Learn framework to analyze student perspectives on information literacy, data interpretation, and computational thinking. The findings inform pedagogical strategies for developing data proficiency in …

Organisational Resilience : A Study Of The Resilience Of Maritime Stakeholders In Ghana, Priscilla Ami Dogbeda Dzokoto

World Maritime University Dissertations

No abstract provided.

Stereo Vision Relative Navigation Of Airborne Vehicles, Scott L. Nykl, Brian Woolley, John Pecarina

AFIT Patents

An automated aerial formation (AAF) system includes an imaging device mounted on an imaging first aircraft that receives reflected energy from an imaged second aircraft. A controller is communicatively coupled to the imaging device and a flight control system of one of the first and the second aircraft. The controller generates a three-dimensional (3D) point cloud based on the reflected energy and identifies a target 3D model in the 3D point cloud. The controller rotates and scales one of a pre-defined 3D model and the target 3D model to find a 3D point registration between the target 3D model and …

Spacecraft Attitude Control Simulator, Bricen S. Rigby

College of Engineering Summer Undergraduate Research Program

The Spacecraft Attitude Control Simulator is a single-axis attitude control platform which is intended to recreate the frictionless space environment in order to test cold-gas thruster control schemes. The overall goal of this research project was to observe settling data from the platform and compare it to simulated data. In practice, the predicted settling time was only 7% larger than observed settling time.

Development Of Python Library For Spacecraft Modeling, Shreya Kale

College of Engineering Summer Undergraduate Research Program

This project involved developing a python library to be used in modeling spacecraft attitude dynamics and control

Attitude Control Of A Flexible Flapping Wing Uav Based On Fuzzy Logic, Reed M. Paulson, Tyson Chen, Diego Del Real, Nico Morrison

College of Engineering Summer Undergraduate Research Program

This project revolves around creating an a attitude controller for a hovering flexible flapping wing UAV that is based on a flying hummingbird. We based our model from a paper by Banazadeh and Taymourtash1 , First replicating the open-loop results using the nonlinear dynamic model and the equations of motion (seen below) while considering aerodynamic loads. Once replicated, we then used fuzzy logic to model the dynamic model. Subsequently, we designed a fuzzy controller to stabilize the hovering mode. We then considered and detailed future work needed to make further progress in this area.

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 …

Computer Based Modeling For Small E-Vtol Propeller Performance, Ege Konuk

Mechanical & Aerospace Engineering Theses & Dissertations

The emerging field of urban air mobility (UAM) offers a novel transportation method for civil, commercial, and military applications. Vertical take-off and landing (VTOL) configurations present challenges for performance prediction during crucial flight operations. An advanced computational framework for predicting propeller performance in electric vertical takeoff and landing (eVTOL) aircraft during transition flight is essential for future concept designs. This research extends the Blade Element Momentum Theory (BEMT) to model propeller behavior at high incidence angles, crucial for eVTOL operation.

The study begins with a review of tilt-wing/rotor configurations for eVTOLs and tackles the complex aerodynamic phenomena associated with rotors …

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 …

Koopman-Based Modeling For Nonlinear Control Of Multirotor Uavs, Simone Martini

Electronic Theses and Dissertations

This PhD dissertation focuses on adopting the emerging Koopman Operator theory for modeling and nonlinear control of multirotor UAVs, focusing specifically on quadrotors for proof-of-concept demonstration purposes.

The Koopman Operator theory is based on the foundation that nonlinear dynamics in the state space may be represented as a linear evolution of some functions in the state space. Thus, using appropriately defined and possibly nonlinear functions of the state variables, called observables, as a new and maybe infinite set of coordinates that are referred to as lifted space, the original nonlinear dynamics appear to be linear. The implications of this theory …

Magnetic Sensor Compensation Utilizing Factor Graph Estimation, Frederic W. Lathrop, Clark N. Taylor, Aaron Nielsen

Faculty Publications

Recently, there has been significant interest in the ability to navigate without GPS using the magnetic anomaly field of the Earth (magnav). One of the key technical bottlenecks to achieving magnav is obtaining an accurate magnetic sensor calibration, taking into account own-ship and sensor effects. The Tolles-Lawson magnetic calibration method continues to be the industry standard and was developed when airborne magnetic survey aircraft were first employed over 70 years ago. In this paper, we present a magnetic calibration algorithm based on a factor graph optimization using inertial measurements as well as inputs from both a vector and scalar magnetometer. …

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 …

F56: Rocket Thrust Vector Control, Ethan Douglas Anderson, Yiming Trent Jia, Sahil Sampat

Mechanical Engineering

This Final Design Review (FDR) report compiles relevant information regarding the Rocket Thrust Vector Control senior project as sponsored by Ethan Anderson from Cal Poly Space Systems (CPSS). Documented in this report is our progress from the months following our Critical Design Review (CDR) completion. This consists of a brief overview of the design our thrust vector control (TVC) system and its subassemblies with design changes noted, a thorough walkthrough of our procurement, manufacturing, and assembly process for creating our verification prototype (including software), a breakdown of how we verified each of our specifications through inspection and testing and the …

Automatic Mass Balancing Of A Spacecraft Attitude Dynamics Simulator With Six Sliding Masses, Amelia J. Gilman

Master's Theses

The goal of this thesis is to investigate automatic mass balancing methods for spacecraft attitude dynamics simulators, create a hardware design for a mass balancing system, and assemble the hardware on the Cal Poly Spacecraft Attitude Dynamics Simulator (SADS). Spacecraft attitude dynamics simulators replicate the torque-free environment of space with ground-based hardware. The SADS is mounted on a spherical air bearing, and includes a pyramid of four reaction wheels. The air bearing allows frictionless, unbounded rotation about the vertical axis, and 30 degrees about the horizontal axes. The torque-free configuration of the SADS can be used to test spacecraft attitude …

Team F16: Autonomous Research Plane, Andrew Sugamele, Andrew Whitacre, Nicholas Toal, Cole Bushur

Mechanical Engineering

The autonomous research plane is a remote-controlled plane used for both in-flight data collection and to explore new manufacturing methods for Design Build Fly, an engineering club on campus. The club does not have the resources or time to implement data collection for their competition plane, so we built a plane in parallel, following similar rules to mimic the work and schedule that the club would use during their season. We first did research and analysis to determine the structure of the plane, geometry of wings, sizing of the tail, and what airfoil to choose. The manufacturing process included making …

Exploring The Feasibility Of The Resonance Corridor Method For Post Mission Disposal Of High-Leo Constellations, Payton G. Porter

Master's Theses

In the upcoming decade, the proliferation of high-LEO constellations is expected to exceed 20,000 objects, yet comprehensive Post Mission Disposal (PMD) strategies for these constellations are currently lacking. With the inherent challenges of efficiently deorbiting satellites from High-LEO orbits, there arises an urgent need to explore innovative approaches. Building upon insights garnered from the ReDSHIFT project and anticipating the proliferation of high-LEO constellations such as OneWeb, TeleSat, and GuoWang, this thesis delves into the potential viability of the Resonance Corridor Method for PMD. The investigation encompasses key metrics, including deorbit timelines and $\Delta v$ requirements to meet regulatory standards or …

A Hardware-In-The-Loop Star Tracker Test Bed, Ashley Haraguchi

Master's Theses

As the use of small satellites for advanced space missions continues to grow, the importance of low mass and cost three-axis attitude stabilization systems increases as well, with these systems requiring high accuracy attitude knowledge. Star trackers provide the most accurate attitude knowledge of any type of attitude sensor, but the high cost, size, and weight of commercial star trackers can be prohibitive to small satellite missions. Many simple star trackers have been developed using commercial off-the-shelf camera sensors and processing hardware, but the challenge remains in testing and characterizing these devices. A common solution is night sky tests, in …

Using Convolutional Neural Networks For Autonomous Drone Navigation, Joshua Jowers

Industrial Engineering Undergraduate Honors Theses

Unmanned Aerial Vehicles (UAVs), more commonly known as drones, serve various purposes, notably in military applications. Consequently, there arises a need for navigation methods impervious to intercepted signals [1]. Previous research has explored numerous solutions, including machine learning. This paper delves into a specific machine learning approach employing a Convolutional Neural Network (CNN) to discern image locations [2]. It elucidates the conversion of a CNN model between two machine learning libraries and presents results from multiple experiments examining parameters and factors influencing the approach's efficacy. These experiments encompass testing different data sources, image quantities, and processing pipelines to gauge their …

System Identification For Motion Control Of Unmanned Aerial Vehicles Platform, Raj Ramesh Agarwal

Theses and Dissertations

Comprehensive research on Unmanned Aerial Vehicles (UAV) system identification for motion control parameters is presented in this thesis, with a focus on the necessity of precise control and improved performance. Using Pseudorandom Binary Sequence (PRBS) and Normally Distributed Random Numbers, it presents a unique technique for excitation of UAV dynamic systems. It also shows how effective random signals are in time-domain identification for precise control in a range of flying circumstances. The piece of research includes a thorough analysis and implementation of various approaches and its further improvements, highlighting the benefits and drawbacks of each. These approaches include the free …

Predictive Ai Applications For Sar Cases In The Us Coast Guard, Joshua Nelson

Cybersecurity Undergraduate Research Showcase

This paper explores the potential integration of predictive analytics AI into the United States Coast Guard's (USCG) Search and Rescue Optimal Planning System (SAROPS) for deep sea and nearshore search and rescue (SAR) operations. It begins by elucidating the concept of predictive analytics AI and its relevance in military applications, particularly in enhancing SAR procedures. The current state of SAROPS and its challenges, including complexity and accuracy issues, are outlined. By integrating predictive analytics AI into SAROPS, the paper argues for streamlined operations, reduced training burdens, and improved accuracy in locating drowning personnel. Drawing on insights from military AI applications …

Distributed Adaptive Control Methods For Uncertain Multiagent Systems With Coupled Dynamics, Islam Aly

Doctoral Dissertations and Master's Theses

For a multiagent system, a major challenge is achieving overall system stability and performance in the presence of not only uncertainties but also coupled dynamics. Another challenge for these systems is designing distributed adaptive controllers with user-assigned positions in this case and defining the convergence rate of the reference model for each agent using only local (i.e., agent-based) information. Discrete-time architectures have an advantage over their continuous counterparts as they can be directly executed on embedded hardware without the need for discretization. Yet, because of the difficulty of ensuring Lyapunov difference expressions, their designs, which are based on quadratic Lyapunov-based …