Engineering Commons^™

Quantum-Powered Battery Scheduling In Modern Distribution Grids, Diba Ehsani

Electronic Theses and Dissertations

The rising need for exploiting a novel and evolved computation is an increasing concern in the power distribution system to address the exponential growth of distribution-connected devices. Scheduling numerous battery energy storage systems in an optimal way is one of the emerging challenges that will be more noticeable as the number of batteries, including residential, community, and vehicle batteries, increases in the grid. This thesis focuses on this topic and offers a necessary component in building the quantum-compatible distribution system of the future. Using a constrained quadratic model (CQM) on D-Wave’s hybrid solver as well as a binary quadratic model …

Data-Driven Approaches For Enhancing Power Grid Reliability, Behrouz Sohrabi

Electronic Theses and Dissertations

This thesis explores the transformative potential of data-driven approaches in addressing key operational and reliability issues in power systems. The first part of this thesis addresses a prevalent problem in power distribution networks: the accurate identification of load phases. This study develops a data-driven model leveraging consumption measurements from smart meters and corresponding substation data to reconstruct topology information in low-voltage distribution networks. The proposed model is extensively tested using a dataset with more than 5,000 real load profiles, demonstrating satisfactory performance for large-scale networks. The second part of the thesis pivots to a crucial safety concern: the risk and …

Consensus-Based Active And Reactive Power Control And Management Of Microgrids, Shruti Singh

Electronic Theses and Dissertations

Microgrids incorporating distributed generation and renewable energy sources offer potential solutions to the energy crisis while modernizing traditional grids. Despite cost-effectiveness in some technologies, financial support remains crucial for expensive ones like PV, fuel cells, and storage technologies. Microgrids bring economic benefits, efficiency, reduced emissions, and improved power quality. Their success hinges on cost reductions in renewables, storage, reliability, and energy management systems, enabling operation both with and without the utility grid.

Economic Dispatch optimizes system costs, considering all constraints. Various methods tackle this problem, including quadratic convex functions, Lagrangian relaxation, and quadratic programming. For microgrids with distributed generators, seamless …

Controllable Language Generation Using Deep Learning, Rohola Zandie

Electronic Theses and Dissertations

The advent of deep neural networks has sparked a revolution in Artificial Intelligence (AI), notably with the creation of Transformer models like GPT-X and ChatGPT. These models have surpassed previous methods in various Natural Language Processing (NLP) tasks. As the NLP field evolves, there is a need to further understand and question the capabilities of these models. Text generation, a crucial part of NLP, remains an area where our comprehension is limited while being critical in research.

This dissertation focuses on the challenging problem of controlling the general behaviors of language models such as sentiment, topical focus, and logical reasoning. …

Design Of Hybrid Inverters Using Wideband Gap Semiconductors For Microgrid Application, Luca Gacy

Electronic Theses and Dissertations

As the world becomes more reliant on renewable energy sources such as solar and wind power, the need for high efficiency high power inverters connected to homes is more relevant than ever. Connecting these renewable energy sources (RES) coupled with an energy storage system (ESS) to the grid through a hybrid inverter, with the highest efficiency and grid stability, is quickly becoming a necessity for the near future. This thesis explores the integration of wide band gap semiconductors for the power stage in these systems, along with the analysis of hybrid inverter topologies and structures. The goal of this thesis …

Robotic Arm Extrusion End Effector, Nicholas Viamin, David Blouin, Savannah Hunt, Nico Figueroa

Interdisciplinary Design Senior Theses

This senior design project aims to enhance the capabilities of the Rotrics AIO Desktop Arm (Dexarm) by designing and implementing an extrusion device capable of smooth and consistent extrusion for 3D printing applications. The project focused on ensuring safety, affordability, and ease-of-use for users, while achieving precise control over the extrusion process. Various mechanical and electrical components were carefully selected to ensure compatibility with the Dexarm and to provide optimal performance. To maintain safety, extensive testing and risk assessments were conducted to minimize any potential hazards associated with the extrusion process. To achieve smooth and consistent extrusion, precise control mechanisms …

Neurogen: Eeg And Near-Infrared Light Stimulation Control System, Arnold Nieto, Jaylinn Solis, Matthew Tamanaha

Interdisciplinary Design Senior Theses

Light stimulation or transcranial photobiomodulation (tPBM) therapy has been shown to be effective when treating patients suffering neurodegenerative diseases such as Alzheimer’s and Parkinson’s disease. While there is currently no cure, light stimulation can help alleviate symptoms for those patient’s suffering from these diseases. With this in mind, the senior design team from last year began a prototype hybrid electroencephalography (EEG) and tPBM device. They implemented a specific wavelength of 810 nanometer (nm) near-infrared (NIR) light emitting diodes (LEDs), with a 16 channel EEG headset from OpenBCI. The device was intended to serve as a potential research tool, with a …

Unsupervised Learning Algorithm For Noise Suppression And Speech Enhancement Applications, Abdullah Zaini Alsheibi

Electronic Theses and Dissertations

Smart and intelligent devices are being integrated more and more into day-to-day life to perform a multitude of tasks. These tasks include, but are not limited to, job automation, smart utility management, etc., with the aim to improve quality of life and to make normal day-to-day chores as effortless as possible. These smart devices may or may not be connected to the internet to accomplish tasks. Additionally, human-machine interaction with such devices may be touch-screen based or based on voice commands. To understand and act upon received voice commands, these devices require to enhance and distinguish the (clean) speech signal …

Reference Frames In Human Sensory, Motor, And Cognitive Processing, Dongcheng He

Electronic Theses and Dissertations

Reference-frames, or coordinate systems, are used to express properties and relationships of objects in the environment. While the use of reference-frames is well understood in physical sciences, how the brain uses reference-frames remains a fundamental question. The goal of this dissertation is to reach a better understanding of reference-frames in human perceptual, motor, and cognitive processing. In the first project, we study reference-frames in perception and develop a model to explain the transition from egocentric (based on the observer) to exocentric (based outside the observer) reference-frames to account for the perception of relative motion. In a second project, we focus …

Deep Learning For Power Flow Estimation And High Impedance Fault Detection, Kun Yang

Electronic Theses and Dissertations

My thesis is divided into two parts.

The first part is: “Optimal Power Flow Estimation Using One-Dimensional Convolutional Neural Network [1]“. Optimal power flow (OPF) is an important research topic in power system operation and control decisions. Traditional OPF problems are solved through dynamic optimization with nonlinear programming techniques. For a large power system with large amounts of variables and constraints, the solving process would take a long time. This paper presents a new method to quickly estimate the OPF results using a one-dimensional convolutional neural network (1D-CNN). The OPF problem is treated as a high-dimensional mapping between the load …

Power System Dynamic Control And Performance Improvement Based On Reinforcement Learning, Wei Gao

Electronic Theses and Dissertations

This dissertation investigates the feasibility and effectiveness of using Reinforcement Learning (RL) techniques for power system dynamic control, particularly voltage and frequency control. The conventional control strategies used in power systems are complex and time-consuming due to the complicated high-order nonlinearities of the system. RL, which is a type of neural network-based technique, has shown promise in solving these complex problems by fitting any nonlinear system with the proper network structure.

The proposed RL algorithm, called Guided Surrogate Gradient-based Evolution Strategy (GSES) determines the weights of the policy (which generates the action for our control reference signal) without back-propagation process …

Artificial Emotional Intelligence In Socially Assistive Robots, Hojjat Abdollahi

Electronic Theses and Dissertations

Artificial Emotional Intelligence (AEI) bridges the gap between humans and machines by demonstrating empathy and affection towards each other. This is achieved by evaluating the emotional state of human users, adapting the machine’s behavior to them, and hence giving an appropriate response to those emotions. AEI is part of a larger field of studies called Affective Computing. Affective computing is the integration of artificial intelligence, psychology, robotics, biometrics, and many more fields of study. The main component in AEI and affective computing is emotion, and how we can utilize emotion to create a more natural and productive relationship between humans …

Digital Beamforming Array Phase Calibration Techniques For Multi-Pass Interferometric Sar, Kelly Cheung

Browse all Theses and Dissertations

Calibration plays a critical role in the optimal performance of algorithms in digital beamforming arrays. Phase incoherency between elements results in poor beamforming with decreased gain and higher sidelobes, leading to a decrease in accuracy and sensitivity of measurements. A similar problem exists in performing multi-pass interferometric SAR (IFSAR) processing of SAR data stacks to generate topological maps of the scene, where phase errors translate to height errors. By treating each SAR image in the data stack like an element of a uniform linear array, this thesis explores several phase calibration techniques that can be used to calibrate digital beamforming …

Bandgap Engineering Of 2d Materials And Its Electric And Optical Properties, Kumar Vishal

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Since their invention in 1958, Integrated Circuits (ICs) have become increasingly more complex, sophisticated, and useful. As a result, they have worked their way into every aspect of our lives, for example: personal electronic devices, wearable electronics, biomedical sensors, autonomous driving cars, military and defense applications, and artificial intelligence, to name some areas of applications. These examples represent both collectively, and sometimes individually, multi-trillion-dollar markets. However, further development of ICs has been predicted to encounter a performance bottleneck as the mainstream silicon industry, approaches its physical limits. The state-of-the-art of today’s ICs technology will be soon below 3nm. At such …

Modeling, Simulation, And Hardware Testing Of A Noise-Canceller Adc Architecture, Ethan R. Rando

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Analog-to-Digital Converters (ADCs) are essential elements of most complex electronic devices. ADCs allow for an analog signal to be converted into the digital domain, and thus interpreted by a digital circuit or model. While ADCs are extremely common, they are not immune from common tradeoffs when being designed and implemented. The most prominent tradeoff when selecting or designing an ADC is whether to pursue a high conversion rate or a high resolution on the digital output. There are some ADC designs that allow for relatively high resolution while maintaining a respectable conversion rate, however these designs often come at the …

Fault Diagnosis And Accommodation In Quadrotor Simultaneous Localization And Mapping Systems, Anthony J. Green

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Simultaneous Localization and Mapping (SLAM) is the process of using distance measurements to points in the surrounding environment to build a digital map and perform localization. It has been observed that featureless environments like tunnels or straight hallways will cause positioning faults in SLAM. This research investigates the fault diagnosis and accommodation problem for a laser-rangefinder-based SLAM systems on a quadrotor. A potential solution of using optical flow as velocity estimate and an extended Kalman filter (EKF) to perform position estimation is proposed. A fault diagnosis method for detecting faults in positional SLAM data or optical flow velocity data is …

Multi-Variable Phase And Gain Calibration For Multi-Channel Transmit Signals, Ryan C. Ball

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A method for software-defined radio array calibration is presented. The method implements a matched filter approach to calculate the phase shift between channels. The temporal stability of the system and calibration coefficients are shown through the standard deviation over the course of four weeks. The standard deviation of the phase correction was shown to be less than 2 deg. for most channels in the array and within 8 deg. for the most extreme case. The standard deviation in amplitude scaling was calculated to be less than 0.06 for all channels in the array. The performance of the calibration is evaluated …

Prediction Of Ka-Band Radar Cross Section With Thz Scale Models With Varying Surface Roughness, Andrew J. Huebner

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Radar cross section (RCS) of electrically large targets can be challenging and expensive to measure. The use of scale models to predict the RCS of such large targets saves time and reduces facility requirements. This study investigates Ka-band (27 to 29 GHz) RCS prediction from scale model measurements at 500 to 750 GHz. Firstly, the coherent quasi-monostatic turntable RCS measurement system is demonstrated. Secondly, three aluminum 18:1 scale dihedrals with surface roughness up to 218 icroinches are measured to investigate how the roughness affects the Ka-band prediction. The measurements are compared to a parametric scattering model for the specular response, …

Merit Study Of Battery Or Hydrogen Energy Storage For Large Scale, Combined Wind And Solar Electricity Generation, Ashley K. Moore

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In the past several years, the energy sector has experienced a rapid increase in renewable energy installations due to declining capital costs for wind turbines, solar panels, and batteries. Wind and solar electricity generation are intermittent in nature which must be considered in an economic analysis if a fair comparison is to be made between electricity supplied from renewables and electricity purchased from the grid. Energy storage reduces curtailment of wind and solar and minimizes electricity purchases from the grid by storing excess electricity and deploying the energy at times when demand exceeds the renewable energy supply. The objective of …

Behavior, Switching Losses, And Efficiency Enhancement Potentials Of 1200 V Sic Power Devices For Hard-Switched Power Converters, Ali Mahmoud Salman Al-Bayati, Mohammad Abdul Matin

Electrical and Computer Engineering: Faculty Scholarship

Semiconductor power devices are the major constituents of any power conversion system. These systems are faced by many circumscriptions due to the operating constraints of silicon (Si) based semiconductors under certain conditions. The emergence and persistence evolution of wide bandgap technology pledge to transcend the restrictions imposed by Si based semiconductors. This paper presents a thorough experimental study and assessment of the performance of three power devices: 1200 V SiC cascode, 1200 V SiC MOSFET, and 1200 V Si IGBT under the same hardware setup. The study aims to capture the major attributes for each power device toward determining their …

A Music-Therapy Robotic Platform For Children With Autism: A Pilot Study, Huanghao Feng, Mohammad H. Mahoor, Francesca Dino

Electrical and Computer Engineering: Faculty Scholarship

Children with Autism Spectrum Disorder (ASD) experience deficits in verbal and nonverbal communication skills including motor control, turn-taking, and emotion recognition. Innovative technology, such as socially assistive robots, has shown to be a viable method for Autism therapy. This paper presents a novel robot-based music-therapy platform for modeling and improving the social responses and behaviors of children with ASD. Our autonomous social interactive system consists of three modules. Module one provides an autonomous initiative positioning system for the robot, NAO, to properly localize and play the instrument (Xylophone) using the robot’s arms. Module two allows NAO to play customized songs …

A Low-Cost, Long-Range, And Solar-Based Iot Soil Quality Monitor, Salvador Garcia, Trina Nguyen, Julian Wong

Interdisciplinary Design Senior Theses

The project objective is to create a low-cost, long-range, and solar-based IoT soil quality monitoring system. The system must transmit packages of data gathered from separate nodes, consisting of two dierent types of sensors, to a centralized gateway receiver to be displayed to the user in an elegant and readable manner. The end goal of the project is to supplement produce grown by large agricultural bodies around the United States without the misuse of water resources. This report presents the need for this system, details the components of the system, and the rationale behind design choices. It serves as a …

Neurogen: Eeg And Near-Infrared Light Stimulation Control System, Karina Sanchez, Sruthi Sakthivel, Michael Bose, Evan Jennings

Interdisciplinary Design Senior Theses

Neurodegenerative diseases, such as Alzheimer’s disease and Parkinson’s disease are widespread, affecting millions of people worldwide. These diseases occur when neurons in the brain or peripheral nervous system progressively lose function and deteriorate. Current pharmacological treatments manage some of the neurological symptoms, but there is no cure yet. Interventions that mitigate or restore loss of function can fill the void until that goal is met. Light stimulation, or transcranial photobiomodulation (tPBM) therapy, can help treat people with neurodegenerative diseases, as it has been shown to improve sleep, attention, memory, and cognitive function.

The objective of this project is to develop …

Ad-Corre: Adaptive Correlation-Based Loss For Facial Expression Recognition In The Wild, Ali Pourramezan Fard, Mohammad H. Mahoor

Electrical and Computer Engineering: Faculty Scholarship

Automated Facial Expression Recognition (FER) in the wild using deep neural networks is still challenging due to intra-class variations and inter-class similarities in facial images. Deep Metric Learning (DML) is among the widely used methods to deal with these issues by improving the discriminative power of the learned embedded features. This paper proposes an Adaptive Correlation (Ad-Corre) Loss to guide the network towards generating embedded feature vectors with high correlation for within-class samples and less correlation for between-class samples. Ad-Corre consists of 3 components called Feature Discriminator, Mean Discriminator, and Embedding Discriminator. We design the Feature Discriminator component to guide …

Classification Of Electropherograms Using Machine Learning For Parkinson’S Disease, Soroush Dehghan

Electronic Theses and Dissertations

Parkinson’s disease (PD) is a neurodegenerative movement disorder that progresses gradually over time. The onset of symptoms in people who are suffering from PD can vary from case to case, and it depends on the progression of the disease in each patient. The PD symptoms gradually develop and exacerbate the patient’s movements throughout time. An early diagnosis of PD could improve the outcomes of treatments and could potentially delay the progression of this disorder and that makes discovering a new diagnostic method valuable. In this study, I investigate the feasibility of using a machine learning (ML) approach to classify PD …

Data-Enabled Distribution Grid Management, Zohreh Sadat Hosseini

Electronic Theses and Dissertations

In 2020, U.S. electric utilities installed more than 94 million advanced meters, which brought the percentage of residential customers equipped with smart meters to 75%. This significant investment allows collecting extensive customer data at the distribution level, however, the data are not currently leveraged effectively to help with system operations. This dissertation aims to use the smart meters’ data to improve the grid’s reliability, stability, and controllability by solving two of the most challenging problems at the distribution level, namely distribution network phase identification and outage identification.

Distribution networks have typically been the least observable and most dynamic and locally …

Learning Approach For Fast Approximate Matrix Factorizations, Haiyan Yu

Electronic Theses and Dissertations

Efficiently computing an (approximate) orthonormal basis and low-rank approximation for the input data X plays a crucial role in data analysis. One of the most efficient algorithms for such tasks is the randomized algorithm, which proceeds by computing a projection XA with a random projection matrix A of much smaller size, and then computing the orthonormal basis as well as low-rank factorizations of the tall matrix XA. While a random matrix A is the de facto choice, in this work, we improve upon its performance by utilizing a learning approach to find an adaptive projection matrix A from a set …

Crossroad - Avoid Crowd Intelligence, Xukun Zhang, Yuzheng Wu, Haochen Zhang

Interdisciplinary Design Senior Theses

Nowadays, waiting takes big chunks of daily-life activity. People may always find themselves facing long queues, waiting in a crowded facility, even when they have tried to avoid peak hours. Heading to a highly populated public area may have felt like heading to a battlefield. Without access to the real-time information of the facility, people start to discover that waiting starts to become an unpredictable event that can sometimes delay their schedule or even worse. This project serves as a solution to tackle this lack of transparency. Crossroad aims to combine facilities’ cameras with micro-controller to see the engagement of …

Jamming Attack Workaround Study, Soren Madsen, Jack Schoen

Interdisciplinary Design Senior Theses

The Internet of Things (IoT) is a fast growing industry with strong footholds in the smart home market featuring devices such as the Amazon Echo, Ring security cameras, smart TVs, and much more. However, it doesn’t stop there; the industrial sector has begun using smart devices for measurement, automated tasks, and time sensitive communication. Many of these devices have become reliant on WiFi technology and are vulnerable to attacks on the security of the protocols involved.

In this paper, we discuss the details of the deauthentication attack on WPA and WPA2 systems and propose a solution for detection and recovery …

Mobile Nanogrid, Daniel Mendoza, Ben Mahony, Charles Ju, Michael Batshon

Interdisciplinary Design Senior Theses

The mobile nanogrid is a standalone mobile power solution which uses a combination of automatic and manual tracking mechanisms to maintain a solar panel's perpendicularity to the sun over the course of the day in order to maximize energy generation. The power can then be consumed by a user or stored. It is designed to be placed on the roof of a vehicle for the recreational camping market to meet the need for mobile power generation. A scaled-down functional prototype was designed in SolidWorks, modeled in MATLAB Simulink, fabricated in the machine shop using a combination of off-the-shelf and custom …