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Articles 301 - 330 of 24437
Full-Text Articles in Entire DC Network
Design And Reliability Analysis Of A Radiation-Tolerant On-Board Computer System For Martian Surface Missions, Jack Ryan
Master's Theses
Space environments present complex challenges for electronic devices, perhaps most notably in the form of radiation effects; the natural protections provided by Earth’s atmosphere and magnetosphere are largely absent in deep space and extraterrestrial environments, making single-event effects (SEE) a critical concern. Although radiation-hardened components offer near-immunity to SEE, they possess tremendous drawbacks in both cost and performance. To circumvent such issues, this thesis investigates the feasibility of leveraging a commercial-off-the-shelf (COTS) device, the AMD KRIA K24 system-on-module (SOM), for use in Martian surface missions.
Detailed models were used to predict SEE rates in the system, and system-level fault tree …
Neural-Network-Based Modeling Of Grid-Forming Inverters, Jacob D. Levesque
Neural-Network-Based Modeling Of Grid-Forming Inverters, Jacob D. Levesque
All Theses
Renewable energy production has grown significantly in recent years and continues to expand, resulting in an increasing number of inverter-based resources (IBRs) in the grid. As the number of IBRs in the grid continues to grow, grid-forming (GFM) inverters are becoming increasingly popular due to their ability to regulate voltage and frequency, providing increased grid stability and enabling islanding. As GFM inverters become more widely used in power systems, accurate and efficient models of their behavior are needed for system design purposes.
Emerging advances in neural networks have led to research on computationally efficient neural-network-based (NN-based) modeling approaches for inverters. …
Introduction To The Special Issue On Computer Modeling For Future Communications And Networks, Wenbing Zhao, Pan Wang
Introduction To The Special Issue On Computer Modeling For Future Communications And Networks, Wenbing Zhao, Pan Wang
Electrical and Computer Engineering Faculty Publications
No abstract provided.
Enhancing Reliable Performance Of Microgrids With Autonomous Control Of Distributed Energy Resources, Sahand Liasi
Enhancing Reliable Performance Of Microgrids With Autonomous Control Of Distributed Energy Resources, Sahand Liasi
All Dissertations
This dissertation presents a comprehensive investigation into enhancing the reliability, efficiency, and autonomous operation of modern power networks through advanced microgrid integration and control strategies. The research addresses critical challenges across three interconnected domains: microgrid control, thermodynamic modeling of heat recovery system (HRS), and optimal distribution network reliability.
In the realm of microgrid control, this work introduces novel methodologies for grid forming inverter-based resources (IBRs). A significant contribution is the development and validation of an "Auto Frequency Change" controller, which drastically reduces microgrid synchronization time with the main grid from several minutes to approximately four seconds, with theoretical potential for …
Safe Control Design For Quadruped Locomotion In Unstructured Environments Using Linear Transfer Operators, Sriram Sundar Krishnamoorthy Shankara Narayanan
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 …
Mitigating Inertial Measurement Unit Drift In Quadcopter Trajectory Tracking Using Kalman Filter Sensor Fusion With Global Positioning Measurements, Juan Sandro Caballero Aguilar
Mitigating Inertial Measurement Unit Drift In Quadcopter Trajectory Tracking Using Kalman Filter Sensor Fusion With Global Positioning Measurements, Juan Sandro Caballero Aguilar
Graduate Theses and Dissertations
Unmanned Aerial Vehicles (UAVs) like quadcopters are widely used in civilian and military applications such as farming, photography, search and rescue missions, and autonomous navigation and motion. The performance and stability of these systems depend on accurate state estimation, which provides real-time information about the vehicle’s position, velocity, and orientation. However, achieving reliable state estimation is challenging due to sensor noise, measurement uncertainty, and inaccurate modeling. Common navigation sensors such as the Global Positioning System (GPS) and Inertial Measurement Units (IMUs) exhibit complementary characteristics. GPS provides absolute position measurements but suffers from noise, multipath effects, and low update rates, while …
Electrical Resilience In Water Treatment Plants: An Extreme Weather And Lightning Protection Study, Genesis Martinez
Electrical Resilience In Water Treatment Plants: An Extreme Weather And Lightning Protection Study, Genesis Martinez
Theses and Dissertations
Water treatment plants (WTPs) are vital infrastructure systems that depend on sensitive electrical, electronic, and control equipment to ensure the continuous supply of safe drinking water and effective wastewater treatment. As global temperatures rise and climate change accelerates, the frequency and intensity of extreme weather events—such as hurricanes, flooding, and increased lightning activity—are becoming more pronounced. These events pose significant risks to the electrical resilience of water treatment facilities, often leading to power outages, equipment failures, grid instability, and prolonged service disruptions. This report explores the impacts of extreme weather, with a particular focus on lightning and electrical surges, on …
Design And Simulation Of Anti-Resonant Hollow-Core Fiber For Sensing Applications, Pravallika Kante
Design And Simulation Of Anti-Resonant Hollow-Core Fiber For Sensing Applications, Pravallika Kante
Theses and Dissertations
This thesis presents the design and simulation of an 8-tube single-ring anti-resonant hollow-core fiber for sensing applications, with particular emphasis on methane gas detection at the fundamental absorption wavelength of 3.3 µm. Conventional solid-core silica optical fibers exhibit strong multi-phonon material absorption beyond 2.5 µm, rendering them fundamentally unsuitable for efficient light guidance and direct gas sensing at mid-infrared wavelengths. Anti-resonant hollow-core fibers overcome this limitation by guiding light predominantly through an air-filled hollow core via the anti-resonant reflecting optical waveguide mechanism, in which the thin silica glass walls of the cladding tubes act as Fabry-Pérot etalons that confine the …
Learning Global Context For Sparse Activity Recognition In Lengthy Recordings With Limited Dataset Size, Zeyu Tang
All Dissertations
This dissertation describes methods to analyze lengthy recordings of data in order to detect sparsely occurring activities. The narrative below describes the progression of research that led to the development of these methods and their generalization into a unified framework. My research started with designing models for dietary monitoring, including detecting meals from day-long recordings and detecting intake gestures from meal-length recordings. Both tasks share some common characteristics: (a) the target event takes only a small portion of data recordings, and (b) there is global context within full-length data recordings that can help a model make better decisions. After finishing …
Versatile Exoskeleton Control Paradigms For Agile Human Locomotion: Task-Agnostic And Stability-Augmented Assistance, Miao Yu
All Dissertations
Lower-limb exoskeletons have shown great potential for assisting human locomotion, but designing controllers that provide assistance across diverse locomotor tasks and under external perturbations remains a major challenge. Many existing controllers for steady-state walking rely on pre-defined reference trajectories, which constrain voluntary human motion and limit adaptability across tasks. Moreover, they usually assume stable walking, while their performance under unstable conditions remains largely unexplored. In addition, existing gait stability augmentation controllers are often reactive rather than proactive to unstable conditions. In this dissertation, we propose control frameworks that preserve voluntary human motion while addressing two major challenges: providing task-agnostic assistance …
Design Of An Extensible And Scalable Data Acquisition System For Pulse Shape Discrimination, Prince John
Design Of An Extensible And Scalable Data Acquisition System For Pulse Shape Discrimination, Prince John
McKelvey School of Engineering Graduate Student Theses & Dissertations
This thesis presents the design and development of a highly scalable, end-to-end data acquisition (DAQ) system for nuclear physics experiments that can be deployed in configurations ranging from a few to thousands of detector channels. The system is built as an extensible platform composed of modular 16-channel chipboards that support a wide range of scintillator and detector types and perform real-time, on-board data sparsification and pulse-shape processing. Three versions of the chipboard have been fabricated to date.
The DAQ architecture is based on a family of analog pulse-shape-processing application- specific integrated circuits (ASICs) developed by the IC Design Laboratory at …
Conditioning Hierarchical Diffusion Transformers On Rf Circuit Parameters, Ethan Morton
Conditioning Hierarchical Diffusion Transformers On Rf Circuit Parameters, Ethan Morton
McKelvey School of Engineering Graduate Student Theses & Dissertations
As modern ML techniques have become increasingly advanced, they have begun to be integrated into wireless RF systems for classification, identification, and spectrum management. Deep Neural Networks (DNNs) enable RF system operators and designers to design more flexible systems with greater robustness to errors and attacks. However, neural networks require significant amounts of properly annotated data to train. Current data labeling methods lack the ability to obtain reliable true labels for circuit properties such as carrier frequency offset (CFO), power amplifier (PA) non-linearity, and in-phase/quadrature (IQ) imbalance. This thesis investigates the efficacy of a novel architecture, RF-Diffusion, for generating high-quality …
Temporal Logic Planning In Semantic Maps Of Unknown Environments Using Tl-Rrt, Dongrui Yang
Temporal Logic Planning In Semantic Maps Of Unknown Environments Using Tl-Rrt, Dongrui Yang
McKelvey School of Engineering Graduate Student Theses & Dissertations
Autonomous mobile robots are increasingly expected to perform complex missions in unstructured environments. Traditional path planning approaches handle simple point-to-point navigation, but struggle with complex tasks that involve temporal and logical orderings of objectives. Linear Temporal Logic (LTL) provides a method for complex missions (e.g., sequential visits to multiple targets or surveillance tasks) in a strict way. This thesis presents an integrated planning framework that enables a robot to satisfy LTL-based task specifications in an unknown environment by combining a Temporal Logic RRT* (TL-RRT*) planner with semantic mapping. The robot builds a semantic map of its environment online using simultaneous …
Robust Hardware Trojan Detection Leveraging Dual‑Domain Features And Stacked Ensemble Learning, Sefatun-Noor Puspa
Robust Hardware Trojan Detection Leveraging Dual‑Domain Features And Stacked Ensemble Learning, Sefatun-Noor Puspa
All Theses
In Cyber-physical systems rely on sensors, communication, and computing, all powered by integrated circuits (ICs). These ICs are vulnerable to malicious hardware attacks, with hardware Trojans being one of the stealthiest threats. Trojans are malicious implants in the circuitry, which are often inserted during design or fabrication stages. This stealthy addition remains dormant until triggered and might cause functional disruptions or sensitive information leakage once triggered. Traditional IC validation methods, such as functional testing and logic analysis, usually fail to capture these subtle anomalies because hardware Trojans are intentionally designed to mimic normal circuit behavior. They often remain dormant under …
Laser-Induced Acoustic Signal Generation, Resonance Characterization, And Optical Sensing In Metallic Plates, Xinghang Zhao
Laser-Induced Acoustic Signal Generation, Resonance Characterization, And Optical Sensing In Metallic Plates, Xinghang Zhao
All Theses
This thesis investigates laser-induced acoustic signal generation, resonance characterization, and optical sensing in metallic plates as a foundational study for damage-sensitive inspection. Rather than presenting a complete defect-detection system, the work focuses on how measurable acoustic responses can be generated, amplified, and interpreted in a controlled laboratory setting. Experiments showed that pulsed-laser excitation can produce strong and repeatable acoustic responses in metallic structures. Repetition-rate sweeping identified narrow resonant responses, including a cantilever resonance at 57.862 kHz and a maximum circular-disk response at an FFT frequency of 48.8 kHz with a laser repetition rate of about 49.1 kHz. High-Q resonances exceeding …
Enhanced Situational Awareness Of Solar Pv Plants For Near Real-Time Planning And Operation In Modern Power Systems, Michael A. Walters
Enhanced Situational Awareness Of Solar Pv Plants For Near Real-Time Planning And Operation In Modern Power Systems, Michael A. Walters
All Theses
Solar photovoltaic (PV) plant development and utilization is increasing worldwide but remains intrinsically challenged by its large dependence on highly variable weather conditions and operating states. This paper presents a framework to leverage three new situational awareness indices (SAIs), namely: weather condition index (WCI) to gauge operational performance based on environmental states, operational complexity index (OCI) to indicate the severity of power generation reductions, and photovoltaic generation index (PVGI) to provide a final determination of the impact on power generation and to bolster situational awareness in planning and operational contexts for solar PV plants. This is accomplished by exploiting the …
Development Of Low-Cost Triaxial Force Sensor For Measurement Of Human-Exoskeleton Interaction Forces, Hamdan Khan Sarvathullah
Development Of Low-Cost Triaxial Force Sensor For Measurement Of Human-Exoskeleton Interaction Forces, Hamdan Khan Sarvathullah
All Theses
Contemporary research suggests that shear force is a major contributor to discomfort and pressure injury. However, the variation of shear forces during human-exoskeleton interaction dynamics is a highly unexplored field. The high cost of commercial triaxial force sensors may be a major factor in the notable lack of research in this field. Therefore, in this paper, we present a low-cost, 3D-printed triaxial force sensor designed specifically to measure the triaxial interaction forces between an exoskeleton and its user. The triaxial force sensor uses Carbon-Black/Silicone Rubber (CB/SR) strings to measure shear forces, whereas the normal force is measured with a Force …
Design And Optimization To Advance Silicon Carbide Modules For Medium Voltage High Power Applications, Ahmed Ismail
Design And Optimization To Advance Silicon Carbide Modules For Medium Voltage High Power Applications, Ahmed Ismail
Graduate Theses and Dissertations
The commercial availability of the first 10 kV silicon carbide (SiC) MOSFET removes the principal semiconductor barrier to medium-voltage power conversion, enabling converter topologies that are structurally inaccessible to silicon IGBT solutions at this voltage class. This dissertation presents the characterization infrastructure, device-level data, and preliminary system-level validation needed to advance the deployment of the third-generation 10 kV SiC MOSFET in converter applications. A custom-built 10 kV double-pulse test platform is developed with a fully documented component-sizing methodology, custom medium-voltage magnetics, and a measurement infrastructure capable of high bandwidth waveform capture at kilovolt common-mode potentials. On this platform, the third-generation …
Simultaneous Carrier, Cargo, And Functional Tracking Of Lipid Nanoparticles, Hannia Vanessa Balcorta Muñoz
Simultaneous Carrier, Cargo, And Functional Tracking Of Lipid Nanoparticles, Hannia Vanessa Balcorta Muñoz
Open Access Theses & Dissertations
Lipid nanoparticles (LNPs) have become effective delivery vehicles in nanomedicine, particularly for nucleic acid-based treatments. However, a major limitation remains in the field regarding the simultaneous monitoring of the nanoparticle carrier, its encapsulated payload, and the resulting functional protein production in both in vitro and in vivo systems. Furthermore, traditional lipophilic dyes employed for labeling LNPs frequently exhibit incompatibility with tissue-clearing methods, such as CLARITY, due to signal loss following lipid removal. This research developed and evaluated a new fluorescent labeling method using CM-DiI, a dye that reacts with thiols, for multimodal tracking of LNPs. CM-DiI was included in the …
Quantifying Spatiotemporal Ev In-Motion Load Dynamics For Flexible Distribution Grid Operations, Travis Newbolt
Quantifying Spatiotemporal Ev In-Motion Load Dynamics For Flexible Distribution Grid Operations, Travis Newbolt
Open Access Theses & Dissertations
The emergence of novel in-motion Electric Vehicle (EV) charging through Dynamic Wireless Power Transfer (DWPT) technology is enabling the transformation of traditional roadway infrastructures into fully integrated Electrified Transportation Networks (ETNs) by the direct coupling of roadways with electric power grids. This paradigm has the potential to improve charging safety, extend driving ranges, reduce EV manufacturing costs through smaller battery sizes, and shift EV charging demand to periods when Distributed Energy Resources (DERs) are more readily available. In addition, the transition to ETNs can improve air quality and reduce noise pollution by displacing fossil fuel consumption from vehicles to centralized …
A Low-Cost Motion Classification System For A Stuffed Animal Using An Imu And Machine Learning, Rachel N. Guynes
A Low-Cost Motion Classification System For A Stuffed Animal Using An Imu And Machine Learning, Rachel N. Guynes
Honors Theses
One of the many fields that has seen the integration of robots is therapy. Zoomorphic robots (ZR) are designed to look and behave like animals to assist in Animal Assisted Therapy (AAT) practices. Studies show that ZRs can provide benefits similar to working with an actual animal; however, their high cost limits their accessibility. This thesis documents the process of building a real-time, low-cost motion classification system that can be attached to a stuffed animal to make it more interactive. Using a Random Forest (RF) classifier, the system identifies movements with approximately 81.67% accuracy.
Increasing The Prediction Accuracy Of Plant Oil Production Processes Through Adjusting The Parameters Of Machine Learning Models, Umidjon Ruziev, M.K. Shodiev, A.T. Rajabov
Increasing The Prediction Accuracy Of Plant Oil Production Processes Through Adjusting The Parameters Of Machine Learning Models, Umidjon Ruziev, M.K. Shodiev, A.T. Rajabov
Chemical Technology, Control and Management
Vegetable oil production is characterized by high variability in output indicators due to nonlinear interactions between raw material parameters, equipment modes, and heat and mass transfer conditions. Existing approaches to applying machine learning in this field, as a rule, do not account for the impact of hyperparameter adjustments on forecasting quality across specific technological stages. The article presents a systematic methodology for adjusting model parameters (Ridge regression, SVR, GBM, LSTM) applied to three key tasks: predicting residual oil content in oil cake, color index during bleaching, and free fatty acid content during deodorization. In a set of 1000 observations, including …
Intelligent Manufacturing Of Edible Oil: From Smart Sensing To Big Data Platform, Ru Jiang, Nadirbek Yusupbekov
Intelligent Manufacturing Of Edible Oil: From Smart Sensing To Big Data Platform, Ru Jiang, Nadirbek Yusupbekov
Chemical Technology, Control and Management
With the rapid advancement of Industry 4.0 technologies, intelligent manufacturing and big data platforms are profoundly transforming the production models of the traditional edible oil industry. The edible oil production process involves multiple complex unit operations such as refining, decolorization, and deodorization, which impose high requirements on process control and product quality monitoring. This paper presents a systematic review of key technological advances in the field of intelligent manufacturing of edible oil, establishing a comprehensive technical framework encompassing four dimensions: smart sensing, artificial intelligence applications, IoT communication, and big data platforms. The review begins by analyzing the global background and …
Reliability Analysis Of Separator Control Systems, D.P. Muxitdinov, O.U. Sattarov, M.Sh. Nematov
Reliability Analysis Of Separator Control Systems, D.P. Muxitdinov, O.U. Sattarov, M.Sh. Nematov
Chemical Technology, Control and Management
This article aims to enhance the reliability, efficiency, and diagnostic capabilities of gas-liquid separators operating in hazardous technological processes. In the study, the separator is considered as a critical functional unit of an industrial system and is analyzed through structural and functional decomposition. The main operating parameters of the separator, including pressure drop (ΔP), separation efficiency and operational state are described on the basis of a mathematical model. In addition, a state model is developed for normal operation, foaming, liquid droplet carryover with the gas flow, and failure conditions. Emphasis is placed on diagnostic and monitoring issues, …
Analysis Of Automatic Control Of The Channels And Ditches Cleaning Mechanism Based On Dynamic Indicators, Nasiba Siraj Amirbayova
Analysis Of Automatic Control Of The Channels And Ditches Cleaning Mechanism Based On Dynamic Indicators, Nasiba Siraj Amirbayova
Chemical Technology, Control and Management
The article deals with the automated design and experimental investigation of reinforced concrete irrigation channels and ditches, their interrelated channel-cleaning mechanisms, which are complex mechatronic systems integrating hydraulic, mechanical, and electronic components. A thorough methodology is suggested, hydrodynamic modeling, combining parametric analysis, and information-based design support to enhance channel concrete cover thickness, geometry, and cleaning system performance. Main structural parameters—involving channel depth, slope, bottom width, and concrete cover—are systematically defined and shown in matrix form to facilitate automated calculation and decision-making. Experimental prototypes and Solid Edge-based digital models are employed to verify the methodology, revealing vital interdependencies between structural parameters, …
Regular Synthesis Algorithms Of Control Devices In Nonlinear Control Systems, Husan Zakirovich Igamberdiyev, Iskandar Yusupovich Abdurakhmanov, Uktam Farkhodovich Mamirov
Regular Synthesis Algorithms Of Control Devices In Nonlinear Control Systems, Husan Zakirovich Igamberdiyev, Iskandar Yusupovich Abdurakhmanov, Uktam Farkhodovich Mamirov
Chemical Technology, Control and Management
This paper examines the development of regularized algorithms for synthesizing control devices in control systems for polynomial objects, described by multidimensional Volterra functional series. The synthesis problem is solved using a two-stage procedure. In the first stage, the optimization problem is initially solved for an open-loop system. The second stage involves determining the parameters of the control device, i.e., its impulse response functions, by using the relationship between the characteristics of the open-loop and closed-loop systems. Regular algorithms are presented for finding the impulse response functions of the control device based on methods for regularizing the solution of operator equations …
Rdm Interval Arithmetic Based Weapon System Evaluation, Konul Imran Jabbarova Phd
Rdm Interval Arithmetic Based Weapon System Evaluation, Konul Imran Jabbarova Phd
Chemical Technology, Control and Management
For solving this issue, the paper considers a hierarchical multi-criteria decision-making problem, where the choice of a company that corresponds best to the criteria is required. Data used in this problem are presented in the form of intervals, which makes it possible to cope with uncertainty in the problem solution. Several companies working in missile production industry are chosen as alternatives for analysis. Evaluation of the selected alternatives is made based on five criteria clusters. More than twenty criteria are taken into account during evaluation.
Solving this problem is achieved with the help of the technique based on computation of …
Structural Decomposition-Based Control Synthesis For Multivariable Systems Using Oblique Projection Operators, Abdukaxxarov Inomjon Ilxom Ugli Mr, Oripjon Olimovich Zaripov, Jasur Usmonovich Sevinov
Structural Decomposition-Based Control Synthesis For Multivariable Systems Using Oblique Projection Operators, Abdukaxxarov Inomjon Ilxom Ugli Mr, Oripjon Olimovich Zaripov, Jasur Usmonovich Sevinov
Chemical Technology, Control and Management
This paper proposes a novel approach to control synthesis for multivariable systems with algebraic constraints using oblique projection operators and their structural decomposition. The method transforms a standard control law into a structured form by decomposing the control input into constraint-satisfying and null-space components. A generalized oblique projector is constructed using a dual matrix, ensuring flexibility in shaping system properties. Furthermore, a recursive decomposition algorithm is developed, allowing the global projector to be represented as a sum of local operators corresponding to subsystem structures. The proposed framework enables modular control design, decoupling of interactions, and efficient implementation for large-scale systems. …
Wavetable Modification In Frequency Domain: Fourier Analysis With Matlab Implementation, Caleb Kortens
Wavetable Modification In Frequency Domain: Fourier Analysis With Matlab Implementation, Caleb Kortens
Senior Honors Theses
One of the challenges in creating computer generated music is producing life-like sounds. Music produced through computer synthesis can often sound thin and synthetic rather than vibrant and energetic. Wavetable synthesis is a method of waveform generation that uses a wavetable, which is a set of single period waves, or frames, that have varying characteristics. This method allows a synthesizer to transition between waveforms to produce a sound with time varying tone and harmonic characteristics. This adds life and movement to computer generated sounds. Wavetable synthesis is often used to imitate actual instruments, but unique wavetables can be created that …
On Time-Series Analysis By Structured Matrix Decompositions With Applications To Signal Direction-Of-Arrival Estimation, Georgios Ierotheos Orfanidis
On Time-Series Analysis By Structured Matrix Decompositions With Applications To Signal Direction-Of-Arrival Estimation, Georgios Ierotheos Orfanidis
Electronic Theses and Dissertations 2020 - Present
Modern autonomous systems operating in highly dynamic, non-stationary environments require reliable inference from short, potentially corrupted time-series measurements, where conventional statistical methods relying on large-sample support and stationarity assumptions become fundamentally inapplicable. This dissertation develops a unified, model-free theoretical framework for time-series analysis, with a particular application to signal Direction-of-Arrival (DoA) estimation, grounded in structured matrix decompositions under both the L2-norm and L1-norm formulations.
We first approach the problem from a conventional viewpoint by carrying out standard matrix analysis directly on Hankel-structured representations of time-series data. In this context, we demonstrate that L1-norm decompositions of Hankel matrices offer strong resistance …