Sliding Mode Control With Chattering Reduction,
2024
Embry-Riddle Aeronautical University
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,
2024
California Polytechnic State University, San Luis Obispo
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,
2024
California Polytechnic State University, San Luis Obispo
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,
2024
California Polytechnic State University, San Luis Obispo
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,
2024
California Polytechnic State University, San Luis Obispo
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,
2024
California Polytechnic State University, San Luis Obispo
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,
2024
University of Arkansas, Fayetteville
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,
2024
Florida Institute of Technology
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,
2024
Old Dominion University
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,
2024
Embry-Riddle Aeronautical University
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 …
Implementation Of Path Planning Methods To Detect And Avoid Gps Signal Degradation In Urban Environments,
2024
Embry-Riddle Aeronautical University
Implementation Of Path Planning Methods To Detect And Avoid Gps Signal Degradation In Urban Environments, Ayush Raminedi
Doctoral Dissertations and Master's Theses
In the modern world, various missions are being carried out under the assistance of autonomous flight vehicles due to their ability to operate in a wide range of flight conditions. Regardless, these autonomous vehicles are prone to GPS signal loss in urban environments due to obstructions that cause scintillation, multi-path, and shadowing. These effects that decrease the GPS functionality can deteriorate the accuracy of GPS positioning causing losses in signal tracking leading to a decrease in navigation performance. These effects are modeled into the simulation environment and are used as part of the path planning algorithm to provide better navigation …
Prediction Of Handling Qualities Deficiencies For Advanced Air Mobility Aircraft,
2024
Embry-Riddle Aeronautical University
Prediction Of Handling Qualities Deficiencies For Advanced Air Mobility Aircraft, Louis Spier
Doctoral Dissertations and Master's Theses
To date, there are hundreds of Advanced Air Mobility (AAM) vehicles under development. Most of these vehicles differ significantly from traditional airplanes and rotorcraft when it comes to configuration and handling qualities. Handling qualities for traditional airplanes and rotorcraft are often very predictable. All AAM concepts currently under development feature some sort of fly-by-wire flight control system. Regulatory agencies already have decades of experience with certifying fly-by-wire airplanes. Fly-by-wire rotorcraft have proven to be significantly more difficult to certify and several flight test accidents have occurred as a result of handling qualities deficiencies, or “cliffs”. To ensure the safe and …
State Omniscience For Cooperative Local Catalog Maintenance Of Close Proximity Satellite Systems,
2024
Embry-Riddle Aeronautical University
State Omniscience For Cooperative Local Catalog Maintenance Of Close Proximity Satellite Systems, Chris Hays
Doctoral Dissertations and Master's Theses
Resiliency in multi-agent system navigation is reliant on the inherent ability of the system to withstand, overcome, or recover from adverse conditions and disturbances. In large part, resiliency is achieved through reducing the impact of critical failure points to the success and/or performance of the system. In this view, decentralized multi-agent architectures have become an attractive solution for multi-agent navigation, but decentralized architectures place the burden of information acquisition directly on the agents themselves. In fact, the design of distributed estimators has been a growing interest to enable complex multi-sensor/multi-agent tasks. In such scenarios, it is important that each local …
Trustable Adaptive Controllers For Multi-Agent Systems With Actuator Dynamics,
2024
Embry-Riddle Aeronautical University
Trustable Adaptive Controllers For Multi-Agent Systems With Actuator Dynamics, Atahan Kurttisi
Doctoral Dissertations and Master's Theses
Multi-agent systems have become a powerful tool for a wide range of applications due to the effective and cheap solutions they offer. Especially during the last decade, they have impacted a wide array of civilian and military applications (e.g., surveillance, reconnaissance, and payload transportation). However, they suffer system anomalies due to the operational and material conditions, which yields degraded performance or even instability. Hence, this dissertation investigates the distributed adaptive control design process for uncertain multi-agent systems with scalar and high-order dynamics in the presence of unknown control effectiveness and actuator dynamics. First, it provides an approach for driving a …
Adaptive Control Of An Aeroelastic System For Active Flutter Suppression And Disturbance Rejection,
2024
Embry-Riddle Aeronautical University
Adaptive Control Of An Aeroelastic System For Active Flutter Suppression And Disturbance Rejection, Patrick Sterling Downs
Doctoral Dissertations and Master's Theses
The future of aircraft design strives for lighter weight, more aerodynamically efficient structures. These improvements may come with the drawback of increased structural flexibility and elevated aeroelastic effects, often resulting in a lower flutter speed. This motivates the implementation of advanced control methods to control aeroelastic systems over a range of flight conditions, suppress and delay the onset of flutter, and compensate for disturbances, actuator dynamics, and unmodeled nonlinear dynamics.
This dissertation first develops a novel method for constructing time-domain simulation models of two and three-dimensional aeroelastic systems, resulting in models that are suitable for the implementation of state-space control …
Adaptive Control For A Class Of Nonlinear, Time Varying Rotational Systems,
2024
Embry-Riddle Aeronautical University
Adaptive Control For A Class Of Nonlinear, Time Varying Rotational Systems, John Zelina
Doctoral Dissertations and Master's Theses
Aerospace systems often exhibit nonlinear, time varying dynamics. Expansive mission profiles, fuel burn or transfer and payload deployments or slung loads can supply additional complexity that can excite the plant dynamics and result in undesirable performance. Because of these often unknown dynamical effects in aerospace systems, an emphasis is placed on controller robustness as significant safety risks are present. Due to the difficulty of predicting uncertainties, robust control can be achieved in two distinct ways. The first approach is to design a control law to be tolerant to a large amount of uncertainty, and the second is to design a …
Farmer Perceptions Of Land Cover Classification Of Uas Imagery Of Coffee Agroecosystems In Puerto Rico,
2024
Embry-Riddle Aeronautical University
Farmer Perceptions Of Land Cover Classification Of Uas Imagery Of Coffee Agroecosystems In Puerto Rico, Jose Cabrera, Blake Neal, Kevin Adkins, Ronny Schroeder, Gwendolyn Klenke, Shannon Brines, Nayethzi Hernandez, Kevin Li, Riley Glancy, Ivette Perfecto
Publications
Highly diverse agroecosystems are increasingly of interest as the realization of farms’ invaluable ecosystem services grows. Simultaneously there has been an increased use of uncrewed aerial systems (UAS) in remote sensing as drones offer a finer spatial resolution and faster revisit rate than traditional satellites. With the combined utility of UAS and the attention on agroecosystems, there exists an opportunity to assess UAS practicality in highly biodiverse settings. In this study, we utilized UAS to collect fine-resolution 10-band multispectral imagery of coffee agroecosystems in Puerto Rico. We created land cover maps through a pixel-based supervised classification of each farm and …
Relative Vectoring Using Dual Object Detection For Autonomous Aerial Refueling,
2024
Air Force Institute of Technology
Relative Vectoring Using Dual Object Detection For Autonomous Aerial Refueling, Derek B. Worth, Jeffrey L. Choate, James Lynch, Scott L. Nykl, Clark N. Taylor
Faculty Publications
Once realized, autonomous aerial refueling will revolutionize unmanned aviation by removing current range and endurance limitations. Previous attempts at establishing vision-based solutions have come close but rely heavily on near perfect extrinsic camera calibrations that often change midflight. In this paper, we propose dual object detection, a technique that overcomes such requirement by transforming aerial refueling imagery directly into receiver aircraft reference frame probe-to-drogue vectors regardless of camera position and orientation. These vectors are precisely what autonomous agents need to successfully maneuver the tanker and receiver aircraft in synchronous flight during refueling operations. Our method follows a common 4-stage process …
Random Forests For Detecting Weak Signals And Extracting Physical Information: A Case Study Of Magnetic Navigation,
2024
Autonomy and Navigation Technology Center, Air Force Institute of Technology
Random Forests For Detecting Weak Signals And Extracting Physical Information: A Case Study Of Magnetic Navigation, Mohammadamin Moradi, Zheng-Meng Zhai, Aaron Nielsen, Ying-Cheng Lai, Aaron P. Nielsen
Faculty Publications
It has been recently demonstrated that two machine-learning architectures, reservoir computing and time-delayed feed-forward neural networks, can be exploited for detecting the Earth’s anomaly magnetic field immersed in overwhelming complex signals for magnetic navigation in a GPS-denied environment. The accuracy of the detected anomaly field corresponds to a positioning accuracy in the range of 10–40 m. To increase the accuracy and reduce the uncertainty of weak signal detection as well as to directly obtain the position information, we exploit the machine-learning model of random forests that combines the output of multiple decision trees to give optimal values of the physical …
Cubesat Reaction Wheel Attitude Control Platform System Architecture,
2024
Embry-Riddle Aeronautical University
Cubesat Reaction Wheel Attitude Control Platform System Architecture, Justin Hartland
Beyond: Undergraduate Research Journal
In the classroom, physics behind spacecraft attitude dynamics and controls is abstract and difficult to comprehend. It is common that students struggle to develop the connection between the math they learn and how it can be applied in the real world. The goal of this project is to design and manufacture a 1U, 3U, and 6U CubeSat testbed for autonomous control systems utilizing reaction wheels. The testbed will include three separate reaction wheels each mounted on its own respective axis to control the attitude in 3 degrees of freedom. The end goal of the CubeSat Control Platform is to be …
