Digital Commons Network^™

Parameter Identification Of A Pi Controller For A Wind Energy Conversion System Based On Dfig, Mariam Hesham, Dina S. M. Osheba, Mahmoud M. Khater

Mansoura Engineering Journal

In this work, three methods are proposed to identify parameters of PI controllers used for wind energy conversion systems based on DFIG. Mathematical model of generator and grid side system is depicted. Three tuning methods; bode-plot, pole-placement, and MATLAB tuner are used for grid side and rotor side converter controllers’ design. Wind turbine system with PI controller parameters obtained using the mentioned method is investigated via MATLAB/SIMULINK under three different scenarios. The wind system is subjected to step wind speed change, random wind speed, and sever symmetrical voltage dip in the grid. The handled comparison illustrates that the pole-placement tuning …

Analog Systems Of Physical Quantities And Their Graph Models In Determining The Parameters Of Mechatronic Modules, Temurbek Omonboevich Rakhimov, Elmira Eshmurod Qizi Raxmanova, Guzal Khujaniyazova

Chemical Technology, Control and Management

This article is dedicated to the analogy systems of physical quantities and their graph models in determining the parameters of mechatronic modules. It presents the general sets and fundamental laws of analogy systems of physical quantities and their elements for determining the parameters of mechatronic modules. Based on the general sets and fundamental laws of analogy systems of physical quantities and their elements, principles have been developed for mechatronic modules with a heterogeneous structure consisting of electrical, magnetic, and mechanical parts. In these modules, the field as a form of matter exists, forming the basis for developing mathematical models to …

Performance Assessment Of Operators Under Digital Simulator-Based Training In Automated Industrial Systems, Kamola Abdullaeva

Chemical Technology, Control and Management

This article proposes a comprehensive approach to training process operators, based on computer simulators integrated with digital twins, SCADA/DCS systems, real production data, and artificial intelligence algorithms. This approach is particularly relevant given the increased requirements for safety, productivity, and reliability of industrial facilities, as human factors are often the main cause of accidents (up to 60-80% of cases). The architecture of the simulator complex is designed to accurately emulate steady-state, transient, and pre-emergency operating modes of equipment, which are not achievable under actual production conditions. The experiment compared the training effectiveness of two groups of operators: one that used …

Investigation Of Nonlinear Magnetic Circuits Of Measuring Transducers With A Special Parameter Distribution Structure, Javhar Sulton O'G'Li Fayzullayev

Chemical Technology, Control and Management

The article proposes a new analytical method for investigating nonlinear magnetic circuits with a special structure of parameter distribution. The method is based on introducing into the system of nonlinear differential equations of such circuits the condition that the second derivative of the magnetic flux along the length of the circuit is equal to zero, as well as on the assumption that one of the geometric parameters of the studied magnetic circuit – the size of the air gap between the ferromagnetic rods, their thickness, width, or the linear value of the number of turns of the distributed excitation winding …

Impact Of Ethanol On The Evolution Of One-Step Synthesized Gold Nanoplates And Nanostars And Their Effects On Raman Signal Enhancement, Ananda Fania, Nonni Soraya Sambudi, Kirana Yuniati Putri, Yuliati Herbani, Affi Nur Hidayah

Makara Journal of Science

Gold nanoplates and nanostars were synthesized from a gold metal salt solution (HAuCl₄) using a one-step synthesis method of ultraviolet C (UVC) light irradiation. The gold salt solution was mixed with ethanol in 6 mL with the following ratios: (1.5:4.5, 3:3, and 4.5:1.5), and subsequently irradiated with UVC light. Changes in localized surface plasmon resonance (LSPR) shifts were observed in real time at 30-min intervals for 2 h. The synthesis process produces gold nanoplates. While gold nanostars were synthesized from a solution of gold salt combined with ethanol, ascorbic acid, and AgNO₃, maintaining a consistent ratio …

Cache-Conscious Sparse Matrix Dense Matrix Multiplication On Gpus, Haoqiang Guo

LSU Doctoral Dissertations

Over the past decade, high-performance deep learning has evolved into a critical research domain, driven by the demand for efficient models and high inference throughput. Deep learning architectures have shifted from stacked convolutional layers to transformer-based models, while pruning techniques and graph-structured data have established sparse matrix–dense matrix multiplication (SpMM) as a fundamental kernel—particularly in graph neural networks (GNNs). Modern GPUs, with their massive parallelism and high-bandwidth memory, offer immense potential for accelerating these workloads. While SpMM implementations using the compressed sparse row (CSR) format remain common to avoid conversion overhead, preprocessing-based methods have recently demonstrated superior potential. In GNN …

Accurate Prediction Of Geometrical Parameters Of An Ultra-Broadband Metamaterial Absorber Using Machine Learning, Md. Rezwan Ahmed, Oishi Jyoti, Pritu Parna Sarkar, Mohammod Abdul Motin, Md. Selim Habib, Md. Samiul Habib

Electrical and Computer Engineering Faculty Publications

In this paper, we systematically demonstrate the design and analysis of a new type of ultra-broadband tunable metamaterial perfect absorber (MPA) comprising a top vanadium dioxide (VO2) based patterned resonating patch, a continuous metallic film at the bottom, and an intermediate dielectric substrate having a thickness of only 0.18 at the center working frequency. The simulation results reveal that the absorber achieves a bandwidth of 7.26 THz, ranging from 5.40 THz to 12.66 THz, with more than 90% absorptance and an average absorption of 98.21% under normal incidence of the incoming THz wave. Furthermore, absorptance exceeding 99% is achieved between …

A Parallel Interval Modeling Framework For Nonlinear Systems: Application To A Modified Duffing Oscillator, Roman Voliansky, Nina Volianska

Northeast Journal of Complex Systems (NEJCS)

The paper presents a mathematical framework for converting nonlinear dynamical systems into parallel forms. This framework replaces the exact system motion equations with interval equations, enabling the representation of nonlinear functions over piecewise linear domains. Such representation enables the description of system motions using linear-like differential equations, which can be analyzed and manipulated using well-known control methods. One such method is eigenvalue analysis, a powerful tool in classical control theory since many techniques rely on the system’s characteristic polynomial and its eigenvalues. We apply this method to define interval system eigenvalues and track their variation during system operation. These eigenvalues …

Integration Of Renewable Energy Networks Into Smart Grid Infrastructure: A Matlab/Simulink-Based Simulation Approach, Saturday Noghayin Osaretin

Electrical Engineering Theses

The rising demand for sustainable and resilient energy systems has accelerated the transformation from traditional power grids toward smart grids integrated with renewable energy networks. This thesis explores the integration of solar energy sources into smart grids to replace conventional fossil-fuel-based generation. A simulation model is developed using MATLAB/Simulink to evaluate the operational performance, stability, and adaptability of the proposed smart grid architecture. Key challenges, including intermittency, synchronization, and bidirectional power flows, are identified, and corresponding solutions, such as energy storage systems, are proposed to address these issues. Simulation results demonstrate enhanced grid stability, reduced carbon footprint, and improved power …

Fpga-Accelerated Computational Photon Counting, Chibueze Onyeador

McKelvey School of Engineering Graduate Student Theses & Dissertations

Fluorescence Lifetime Imaging Microscopy (FLIM) is a powerful tool for biomedical re- search. It leverages fluorescence of biological samples to visualize and characterize biological dynamics and molecular interactions. FLIM utilizes fluorescence lifetime, the average time a molecule stays in its excited state after absorbing a photon, to investigate the dynamics of biological samples.

Ultra-fast and precise (ps-ns) timing fluorescence acquisition techniques suffer from different trade-offs. Some methods suffer from high dead times, decreased accuracy in fluorescence lifetime calculations, and high data volumes and transfers. Finding a new method that can provide the best performance while experiencing low dead times, adequate …

Development Of An Iot-Based Energy Theft Detection System For A Single-Phase Smart Meter, Ojo Julius Oladele, Funso Kehinde Ariyo, Samson Oladayo Ayanlade, Ayooluwa Peter Adeagbo, Ismail Adeniyi Adeleke

Al-Bahir

Electricity theft causes annual global losses exceeding $96 billion, severely impacting distribution networks. This paper presents a novel IoT-based system integrating current differential sensing, physical tamper detection, and edge-cloud analytics to detect energy theft in single-phase smart meters. The design employs three ACS712 current sensors to monitor Kirchhoff-compliant current flow at the grid pole, meter input, and load output, coupled with a PIR sensor for cabinet intrusion. A SIM800L GSM module enables real-time theft alerts and remote disconnection, while closed-loop control autonomously restores power after tamper resolution — a feature absent in prior GSM-only systems. An Android application provides geotagged …

Puf-Based Digital Money With Propagation-Of-Provenance And Offline Transfers Between Two Parties, Benjamin Bean, Cyrus Minwalla, Eirini Eleni Tsiropoulou, Jim Plusquellic

Electrical and Computer Engineering ETDs

Building on prior concepts of electronic money (eCash), we introduce a digital currency where a physical unclonable function (PUF) engenders devices with the twin properties of being verifiably enrolled as a member of a legitimate set of eCash devices and possessing of a hardware-based root-of-trust. A hardware-obfuscated secure enclave (HOSE) is proposed as a means of enabling a PUF-based propagation-of-provenance (POP) mechanism, which allows eCash tokens (eCt) to be securely signed and validated by recipients without incurring any third party dependencies at transfer time. The POP scheme establishes a chain of custody starting with token creation, extending through multiple bilateral …

Stability Analysis Of Thermohaline Convection With A Time-Varying Shear Flow Using The Lyapunov Method, Kalin Kochnev

Honors Scholar Theses

This work applies the Lyapunov method to identify instabilities and compute the growth rate of a linear time-varying system. The linear system studied describes cold fresh water on top of hot salty water with a periodically time-varying background shear flow. A time-dependent weighting matrix is employed to construct a Lyapunov function candidate. The resulting linear matrix inequalities are discretized in time using the forward Euler method. As the number of temporal discretization points increases, the growth rate predicted by the Lyapunov method or Floquet theory, used for comparison, will converge to the same value obtained from numerical simulations. Furthermore, the …

Fedchae: Federated Learning With Client Clustering And Hybrid Adaptive Engagement, Chaeeun Park

Electrical and Computer Engineering ETDs

As machine learning adoption expands, data privacy concerns have grown significantly. Federated Learning (FL) addresses this challenge by allowing clients to train locally and share only their model parameters with the server. However, conventional FL methods such as FedAvg suffer from high communication overhead, as all clients must participate in every global round.

This paper proposes FedChae (Federated Learning with Client Clustering and Hybrid Adaptive Engagement) to balance communication efficiency and model accuracy. FedChae alternates between Grouping Rounds, where all clients perform clustering, and Conventional Rounds, where one client per cluster updates the model.

Simulations with 100 clients using Multi-class …

Graph Based Planning With Guarantees, Trazon Tyrik Jimerson

Mechanical Engineering ETDs

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

Design And Development Of Evacuated Photovoltaic-Thermal Systems For Efficient Cogeneration Of Heat And Electricity, Behnam Roshanzadeh

Mechanical Engineering ETDs

In conventional PV systems, most of the solar energy is dissipated into the environment as heat. Accordingly, hybrid Photovoltaic-thermal systems have been developed to utilize the waste heat from PV cells for various thermal applications. However, most PVT systems suffer from low thermal performance compared to solar thermal collectors, as the absorber plate in PVT systems is partially or fully covered by PV cells. This dissertation focuses on improving the thermal performance of PVT systems by introducing the evacuated PVT systems.

An evacuated-tube PVT system was designed and simulated for domestic hot water supply. The evacuated-tube PVT system demonstrated 40% …

A Bump Hunting Approach To Finding Interpretable Data Pockets, Tushar Ojha

Electrical and Computer Engineering ETDs

This dissertation approaches the problem of extracting simple interpretations from local regions of data. This is sometimes called bump hunting because the local regions of interest have a high concentration of a particular output value. This work develops a bump hunting method for discrete-valued tabular data where each bump is modeled by a rectangular region of the input data space so its rule-based description admits a simple logical interpretation that can inform decisions. This method is designed for labeled data where each input feature has a distinct meaning that may or may not be related to the output, and the …

Parameter Informed Reinforcement Learning For Vehicle System Identification, Nathan Schaff

Doctoral Dissertations and Master's Theses

Accurate system identification is essential for modeling and controlling vehicle dynamics. This dissertation explores the application of Parameter Informed Reinforcement Learning (PIRL) as a novel approach to system identification (SYSID). PIRL integrates prior system knowledge, such as physical parameters, into reinforcement learning (RL) frameworks to improve estimation accuracy. The study begins with an overview of traditional SYSID methods and then introduces PIRL as a modification of standard RL. The research applies PIRL to short-period aircraft dynamics, demonstrating its effectiveness in both offline and online learning frameworks. The dissertation then further explores PIRL’s utility in an indirect model reference adaptive control …

A Predictive Model For Multi- Week Respiratory Risk From Red Tide On Florida’S Gulf Coast., Elmer S. Ochaeta

Computer Science and Engineering Faculty Publications

Florida’s Gulf Coast red tide (Karenia brevis) can put toxins into the air, making people cough, irritating the throat, and worsening asthma or other breathing problems especially when winds blow from the ocean toward the beach. Right now, most public updates don’t really help with the question people actually ask when planning a weekend or vacation: “Will going to or close to the beach be risky in the next few weeks?”.

In this project, I build a weekly early warning system that estimates respiratory risk for specific beaches and predicts that risk 2 to 4 weeks ahead. The study covers …

Developing A Waste-To-Energy Assessment Framework Integrating Engineering And Policy Dimensions Using A Triple Bottom Line Approach, Izech Brian O. Edwin, King Harold A. Recto

Electronics, Computer, and Communications Engineering Faculty Publications

The management of municipal solid waste (MSW) in swiftly urbanizing Philippine cities has emerged as a critical concern in both energy and governance. Dependence on landfills is approaching critical thresholds as disposal sites near saturation, transportation costs escalate, and host communities increasingly resist garbage transfers. In response, this study proposes a comprehensive Waste-to-Energy (WtE) assessment framework that integrates engineering evaluation with policy and stakeholder analysis to support sustainable decision- making.

Using Baguio City as a case study, the framework applies a Triple Bottom Line (TBL) approach to evaluate three waste management scenarios: (1) current landfill-dominated practices, (2) engineered landfill with …

Iso-Detr: A Novel Detection Transformer For Industrial Small Object Detection, Faisal Saeed, Anand Paul

School of Public Health Faculty Publications

Effectively detecting and assessing real-time structural and ecological parameters in contemporary manufacturing environments poses significant challenges, particularly in identifying minute objects within product images. The swift evolution of the industrial sector underscores the necessity for intelligent manufacturing environments to uphold stringent product quality standards. However, accelerating production processes at high speeds heightens the risk of defective product outcomes. This research addresses the challenges inherent in small object detection within industrial contexts, proposing an innovative detection transformer model tailored to modern manufacturing environments. The proposed model integrates a feature-enhanced multi-head self-attention block (FEMSA), merging cross-channel communication network and multiple multi-head self-attention …

Measurement-Based Dynamic Load Model Parameterization Via A Stacked Long Short-Term Memory - Deep Neural Network, Zach H. Smith

All Theses

Increases in distributed generation and changes to predominate load types in modern power systems are driving the need for updated or newly developed dynamic load models. Accurate load modeling is necessary for transmission planning and operation, post-mortem analysis, and inter-regional transfer studies. The most widely used dynamic load model is the WECC Composite Load (CMLD). The CMLD model is an aggregation of substation impedance, under voltage and frequency controls, dynamic motor loads, and static loads. Parameterizing dynamic load models, especially composite models with high parameter counts like the CMLD, is can be difficult. This work proposes a measurement-based, machine learning …

Ai-Optimized Resource Management In Next-Gen Wireless Networks, Fatemeh Lotfi

All Dissertations

Next-generation wireless networks must deliver highly adaptive, scalable, and intelligent connectivity to satisfy the heterogeneous demands of emerging services, including enhanced mobile broadband, massive machine-type communications, and ultra reliable low latency applications. The Open Radio Access Network (O-RAN) paradigm has emerged as a key enabler of this vision, introducing openness, virtualization, and artificial intelligence (AI)-driven control into the RAN ecosystem. O-RAN’s disaggregated architecture facilitates multi-vendor interoperability and empowers intelligent management through the RAN Intelligent Controller (RIC). However, achieving real-time, autonomous, and generalized optimization in such a dynamic environment remains a significant challenge due to its distributed nature, non-stationary traffic, and …

Adaptive Deep Learning In Physical Layer Applications, Ali Owfi

All Dissertations

Traditionally, signal processing models in communication systems have been designed based on solid foundations in statistics and information theory, often assuming linearity and optimizing for simplified models. However, real-world communication systems exhibit numerous imperfections and non-linearities that traditional linear models struggle to capture accurately. Deep Learning (DL)-based approaches, unconstrained by rigid mathematical models, have shown promise in optimizing system performance by accommodating specific hardware configurations and dynamic channel conditions as an alternative to the traditional methods. Despite all the recent research efforts on DL-based methods for physical layer applications, DL models have still not been widely applied to physical layer …

Position Sensor Offset Fault Calibration In Speed-Regulated Pmsm Drives, Ujala Anuradhi Maha Gamage

Masters Theses

Speed regulation of electro-mechanically actuated systems is common across broad application segments, including industrial and residential sectors. The increasing demand for efficient energy conversion has made permanent magnet synchronous machines (PMSM) a preferred choice in modern applications. Vector controlled PMSMs in speed regulation mode being the dominant form of control, accurate speed and position measurement is crucial. However, a misalignment in the position sensor with respect to the true rotor zero position in speed regulated PMSM drives leads to inefficient energy conversion with the possibility of unstable motor behavior. The considered position sensor offset error fault, under severe fault modes, …

Cattlefever: An Automated Cattle Fever Estimation System, Trong Thang Pham, Ethan Coffman, Beth Kegley, Jeremy G. Powell, Jiangchao Zhao, Ngan Le

Electrical Engineering and Computer Science Faculty Publications and Presentations

Farmers face the critical challenge of monitoring cattle well-being for both ethical and economic success, relying on signals like body temperature and facial expressions to assess their animals' health. However, these indicators have traditionally relied on human observation with manual measurement, which is time-consuming and subjective. Despite this clear need, no automated system currently exists for monitoring cattle body temperature, and available datasets remain limited in scope. To address these challenges, we make two key contributions: (i) We introduce CattleFace-RGBT, a novel RGB-Thermal (RGB-T) Cattle Facial Landmark dataset consisting of 2,300 paired RGB and thermal images (4,600 images in total), …

Editable 4d Gaussian Splatting: Scalable And Consistent Video Editing Via Uv-Texture Decomposition, Shuai Lyu

All Theses

Dynamic 3D videos are now widely used in VR, AR, and telepresence, where users often want to change the style or appearance of objects such as clothing over a whole sequence. However, editing such dynamic 3D content is still hard, because appearance, geometry, and motion are tightly coupled, so even a simple color change must stay consistent in all views and at all time steps. Existing editing methods based on 4D Gaussian Splatting often work in a frame-by-frame way, which is slow and makes it difficult to keep temporal and multi-view consistency.

This thesis proposes Editable-4DGS, a representation-centric framework that …

Design And Optimization Of High-Frequency Medium-Voltage Dual Active Bridge Dc/Dc Converter Using Sic Device, Hui Cao

Graduate Theses and Dissertations

High frequency Dual Active Bridge (DAB) converters have become a key enabling technology in medium- and high-power applications such as renewable energy integration, electric vehicle fast charging, and emerging DC power distribution systems. However, when operating at high power and high frequency, DAB converters face critical challenges including limited soft-switching range, uneven semiconductor loss distribution, deadtime-induced resonance, switching-frequency constraints of wide-bandgap (WBG) devices, and transformer DC bias during dynamic transitions. This dissertation addresses these challenges through advancements in modulation strategies and converter architecture. First, an enhanced triple-phase-shift (E-TPS) modulation scheme is proposed to achieve balanced switching and conduction losses across …

Solar Powered Conservation: The Effects Of Solar Photovoltaic Facilities On Avian Community Composition, Michael Christopher Ferrara

Graduate Theses and Dissertations

The expansion of solar photovoltaic energy infrastructure is transforming landscapes worldwide. Increasingly, facilities are planted with native vegetation, yet how vegetation characteristics and landscape variables shape wildlife communities in solar facilities remains poorly understood. Because avian populations have been in decline and are sensitive to habitat changes, understanding how solar facilities influence avian communities is important. In Chapter 1, we used autonomous recording units, local vegetation measurements, and land use and land cover data to quantify how avian community occupancy is influenced by solar cover in solar facilities and comparable reference sites. We used a Bayesian multi-species occupancy model to …

Study And Simulation Of Model-Reference Adaptive Control Via The Heffron-Philips Model For Enhanced Power System Stability, Laila Ayman Dallol

Graduate Theses and Dissertations

Improving power transmission and quality has been an area of research interest over the past decades and was improved using renewable energy resources, mainly wind, and solar generation. Renewable energy penetration into power grids aims to replace some traditional synchronous generators, affecting the overall power system with reduced gas emissions that help with climate change and pollution issues. However, renewable generation in power systems ranging from microgrids to national grids is subjected to large disturbances that affect its transient stability, which is measured by its critical clearing time. As increased amounts of renewable generation connected to power systems have resulted …