Electrical and Computer Engineering
Permanent URI for this collection
Browse
Recent Submissions
Item Uncertain Interval Systems with Application to Separately Excited DC Motor and DC-DC Converters(2024-01-01) Kintali, Narendra; Cheok, Ka C; Cesmelioglu, Aycil; Llamocca, Daniel; Sangeorzan, Brian PElectric drive systems in automobiles, aircraft, and maritime crafts havesignificantly advanced due to changes in hardware and software applications. Drive systems consisting of multidisciplinary subsystems often post non-trivial control problems that must be overcome. For example, redundant input systems related to a separately excited DC motor (SEDCM) or highly varying gains related to DC-DC converters. This thesis introduces a novel approach utilizing an optimization scheme to transform the redundant input process into an uncertain interval system. An armature voltage minimization scheme was developed for the SEDCM to address these redundancies and uncertainties. The comprehensive analysis and feedback control design for an uncertain interval optimal redundant input system is a significant departure from traditional methods, such as Root Locus. The Kharitonov stability criterion is used to analyze the interval systems and determine the parameter boundaries for the controller gains. At the same time, the Root-Locus method is employed to visualize the stable regions of the controller parameters. Next, the Lyapunov stability criterion-based adaptive controller is designed to guarantee stability and tracking for the optimal redundant input systems. For illustration, a PI-controlled separately excited DC motor (SEDCM) will be used. The proposed uncertain interval technique is extended to analyze and design a robust PI controller for DC-DC power electronic converters. The results unify the control design for the buck, boost, and buck-boost converters.Item Multi-Objective Optimal Routing Schemes for High Mobility Vehicular Networks: A Path to Efficiency(2024-01-01) Alolaiwy, Muhammad Musaad M; Zohdy, Mohamed A; Kaur, Amanpreet; Louis, Steven; Rugge, EricaTechnological advancements in wireless communication networks have enabled futuristic applications that support massive device access and pervasive communications. Moreover, vehicular networks in Intelligent Transportation Systems (ITS) require efficient communication and routing schemes to accommodate Electric and Flying Vehicles (EnFVs). A centralized approach is often flawed due to the high mobility and dynamic nature of device movement. Therefore, efficient and novel solutions are required to provide connectivity to EnFVs without any centrally connected unit. Our main focus in this study is to enable a faster, better, and improved communication platform for EnFVs, support a wide range of applications.Item Uncertain Interval Systems with Application to Separately Excited DC Motor and DC-DC Converters(2024-01-01) Kintali, Narendra; Cheok, Ka C; Cesmelioglu, Aycil; Llamocca, Daniel; Sangeorzan, Brian PElectric drive systems in automobiles, aircraft, and maritime crafts havesignificantly advanced due to changes in hardware and software applications. Drive systems consisting of multidisciplinary subsystems often post non-trivial control problems that must be overcome. For example, redundant input systems related to a separately excited DC motor (SEDCM) or highly varying gains related to DC-DC converters. This thesis introduces a novel approach utilizing an optimization scheme to transform the redundant input process into an uncertain interval system. An armature voltage minimization scheme was developed for the SEDCM to address these redundancies and uncertainties. The comprehensive analysis and feedback control design for an uncertain interval optimal redundant input system is a significant departure from traditional methods, such as Root Locus. The Kharitonov stability criterion is used to analyze the interval systems and determine the parameter boundaries for the controller gains. At the same time, the Root-Locus method is employed to visualize the stable regions of the controller parameters. Next, the Lyapunov stability criterion-based adaptive controller is designed to guarantee stability and tracking for the optimal redundant input systems. For illustration, a PI-controlled separately excited DC motor (SEDCM) will be used. The proposed uncertain interval technique is extended to analyze and design a robust PI controller for DC-DC power electronic converters. The results unify the control design for the buck, boost, and buck-boost converters.Item The Characterization of Phase Center of Multi-band GNSS Antenna and the Design of V2V Antenna, along with Channel Analysis in Rural Propagation Scenarios(2024-01-01) Liu, Ran; Aloi, Daniel N.; Kaur, Amanpreet; Schmidt, Darrell; Fuchs, AndreasThe wireless communication network has been vastly improved in the past decades. A high-precise positioning system and reliable wireless network has become an essential part of our daily life, especially Cellular Vehicle-to-Everything (C-V2X). It got most benefit development in Telematics Control Unit (TCU) of Vehicle E/E architecture. The TCU is main including the positioning and wireless connectivity. This research work focus on the automotive multi-band GNSS positioning antenna and Vehicle-to-Vehicle connectivity antenna.Item Uncertain interval systems with application to separately excited dc motor and dc-dc converters(2024-01-01) Kintali, Narendra; Cheok, Ka C; Cesmelioglu, Aycil; Llamocca, Daniel; Sangeorzan, Brian PElectric drive systems in automobiles, aircraft, and maritime crafts havesignificantly advanced due to changes in hardware and software applications. Drive systems consisting of multidisciplinary subsystems often post non-trivial control problems that must be overcome. For example, redundant input systems related to a separately excited DC motor (SEDCM) or highly varying gains related to DC-DC converters. This thesis introduces a novel approach utilizing an optimization scheme to transform the redundant input process into an uncertain interval system. An armature voltage minimization scheme was developed for the SEDCM to address these redundancies and uncertainties. The comprehensive analysis and feedback control design for an uncertain interval optimal redundant input system is a significant departure from traditional methods, such as Root Locus. The Kharitonov stability criterion is used to analyze the interval systems and determine the parameter boundaries for the controller gains. At the same time, the Root-Locus method is employed to visualize the stable regions of the controller parameters. Next, the Lyapunov stability criterion-based adaptive controller is designed to guarantee stability and tracking for the optimal redundant input systems. For illustration, a PI-controlled separately excited DC motor (SEDCM) will be used. The proposed uncertain interval technique is extended to analyze and design a robust PI controller for DC-DC power electronic converters. The results unify the control design for the buck, boost, and buck-boost converters.Item The characterization of phase center of multi-band gnss antenna and the design of v2v antenna, along with channel analysis in rural propagation scenarios(2024-01-01) Liu, Ran; Aloi, Daniel N.; Kaur, Amanpreet; Schmidt, Darrell; Fuchs, AndreasThe wireless communication network has been vastly improved in the past decades. A high-precise positioning system and reliable wireless network has become an essential part of our daily life, especially Cellular Vehicle-to-Everything (C-V2X). It got most benefit development in Telematics Control Unit (TCU) of Vehicle E/E architecture. The TCU is main including the positioning and wireless connectivity. This research work focus on the automotive multi-band GNSS positioning antenna and Vehicle-to-Vehicle connectivity antenna.Item Novel Piezoelectric Biosensor Based on SARS-CoV-2 (COVID-19) Spike Antibody for Coronavirus (Covid-19) Detection(2022-01-01) Alromithy, Fares Sulaimin; Zohdy, Mohamed; Auner, Gregory; Kamel-ElSayed, Suzan; Das, Manohar; Kaur, AmanpreetAt the end of December 2019, the novel coronavirus SARS‐CoV‐2 appeared in Wuhan, China. The World Health Organization released a global health emergency declaration based on growing case notification rates in several locations worldwide. Therefore, sensitive, specific, rapid, and deliverable diagnostic monitoring is vital for making proper decisions on treating and isolating infected patients, which will help prevent the spread of infectious diseases. The surface Acoustic Wave (SAW) biosensor provides a unique, highly sensitive electrical approach to biomolecule detection and cell growth. For this study, a novel SAW sensor is developed, and the mass sensitivities are tested to detect the SARS‐CoV‐2 by attaching the SARS-CoV-2 spike antibody immobilized on the sensor surface. First, a two-dimensional (2D) and a three-dimensional (3D) finite element model were developed based on a realistic device to obtain a complete characterization of the senor. Then, the AlN/Al2O3 fabricated sensor was tested and ultrasonically rinsed in preparation for silanization. After depositions of (APTMS) on the sensor by the Chemical Vapor Deposition method, the antibodies were immobilized on surfaces with the aid of a crosslinker (EDC) and (Sulfo-NHS). Finally, the SARS-CoV-2 was introduced to the sensor, and the attachment of the immobilized antibody was tested and evaluated. The sensor was tested and characterized by Raman spectroscopy and the vector Network Analyzer. Finally, our device was able to detect the virus in real-time time (within two to three minutes), confirming its high sensitivity and selectivity with regard to the SARS-CoV-2 virus.Item A High-Speed, Light Weight Hardware Architecture for H.264- Compatible Compression on an FPGA(2023-01-01) Tayyebi, Azam; Hanna, Darrin M; Louie, Geoffrey; Alawneh, Shadi G; Cesmelioglu, AycilVideo compression is a technique that reduces and removes spatial and temporal redundancy of video data, resulting in a reduction in transmission time and communication bandwidth across a network and efficient storage. H.264, a widely adopted video compression standard, is the result of collaborative efforts between the ISO (International Organization for Standardization) Moving Picture Experts Group (MPEG) and the ITU (International Telecommunication Union) Video Coding Experts Group (VCEG). H.264 uses an array of algorithms for coding digital video to achieve better compression efficiency compared to previous standards. However, this efficiency increase comes at the cost of higher computational complexity for H.264 encoders. This thesis design and implement an H.264-compatible intra-frame video encoder on FPGA. The encoding algorithms, like intra prediction, transform, quantization, and entropy coding, are initially implemented and tested in MATLAB. Later, these algorithms are translated into VHDL language and evaluated through timing simulations vi in Vivado. The FPGA implementation is then tested using various input pixel sizes and video resolutions across multiple FPGA devices. The encoder supports all video resolutions and frame rates.Item GPU-Based Accelerated Algorithms for the Power Flow Calculation(2023-01-01) Zeng, Lei; Alawneh, Shadi G.; Cesmelioglu, Aycil; Yang, LianXiang; He, Ping; Arefifar, Seyed AliPower flow (PF) calculation is critical for power systems, as the development of multiple energy supplies. Power system modeling and analysis have been challenging on power engineers and leading to great pressure for the PF calculation. For the safety, stability and real-time response in grid operation, grid planning and analysis of the power system, it is urged to require designing high-performance computing methods, accelerating PF calculation, obtaining the voltage magnitude and phase angle of buses inside the power system, and coping with the increasingly complex large-scale power system. The PF algorithm is, generally, classified into the iterative and direct methods in the perspective of numerical methods. As for iterative method, a pre-conditioner is required to be designed to reduce the condition number of sparse Jacobian matrix toimprove convergency of the power system. Although the iterative method can save much memory and solve some large-scale sparse linear equations, the PF solver severely depends on the complicated pre-conditioner of the Jacobian matrix. Usually, the PF calculation cannot get a convergent solution without validating the pre-conditioner, repeatedly. For direct method, the traditional sequential, the Newton-Raphson (NR) algorithm will consume much of the computing resource and take a long time to converge on solving large-scale sparse linear equations of the power system. To address these issues, the GPU-based parallel computing architecture, singleGPU, and multi-GPUs, was proposed to take advantage of multi-thread, task parallelism and data parallelism, accelerating the PF calculation. Also, the utilization of GPUDirect technology enhances communication efficiency and significantly reduces data transmission overhead, leading to superior performance improvements compared to the traditional sequential methods.Item Design and Control of a High-Efficiency System for Electric Air Taxis Using MPC And LQR Control, and GAN-Based Power Electronics with Optimized Lithium-Sulfur Battery Management(2024-01-01) Khan, Ahmad Ali; Zohdy, Mohamed A; Rawashdeh, Osamah; Schmidt, Darrell; Barber, GaryLithium-sulfur (Li-S) batteries are a new type of battery that could revolutionize the way we store energy. They have the potential to deliver much more energy than current lithium-ion batteries, which are used in everything from electric cars to smartphones.Item Disturbance Accommodating Control of an Automotive Transmission Torque Converter Clutch System(2024-01-01) Perkins, Todd Addison; Das, Manohar; Kobus, Chris; Olawoyin, Richard; Arefifar, S. Ali; Tomlin, KasaundraModern automotive drivelines are facing increasing pressure to improve overall efficiency while maintaining vehicle comfort and performance. This thesis presents several new ways to control the torque converter clutch in an automotive automatic transmission in such a way they improve driveline system efficiency while maintaining its comfort. This efficiency improvement is accomplished by extending the clutch’s application conditions to a lower speed where the environment is harsher than is possible with the current class of controllers.Item Nonlinear Discrete-Time Control of Modern Power Converters with Robust Adaptive Observer(2023-01-01) Hernandez, Mauricio E.; Zohdy, Mohamed A.; Kruk, Serge; Ganesan, Subra; Edwards, WilliamControl systems are an integral part of modern society, crucial to the performance of these systems is the accurate mathematical model representation of the physical systems. However, every physical system is subject to external factors that over time can change its characteristics. Therefore, to adapt the mathematical model representation of the plant over time a State Observer or State Estimator is often used, which would be the main topic of my research. A ZETA Power converter is a type of switch mode power supply that offers high efficiency in addition to various advantages, among some is its low output ripple which is desired for powering modern VLSI electronics. However, due to its composition (non-linear and fourth order), controlling the dynamics could be complex. With the advances in microprocessing and their economical affordability now, implementing the control scheme of a Zeta converter in the discrete time domain makes it an ideal solution for control implementation, given the lack of research regarding discrete-time control for Zeta Power Converters, state space observers, and adaptive state estimation, this dissertation research aims to identify a novel way of controlling Zeta Converters using adaptive state observers and state feedback in the discrete-time domain that yields robustness in the presence of plant uncertainties that meets certain criteria. The results documented in this dissertation confirm but also outline the limitations of such nonlinear discrete-time domain controller state-feedback from a robust and adaptive full-state observer/estimatorItem Design of a Compact Multi-Band (Cellular 5g/GNSS/V2x) Antenna and Rigorous Analysis of Antenna Performance on Glass Roofs for Vehicular Platforms(2023-01-01) Ibrahim, Ahmad Abu Elhassan Salih; Aloi, Daniel N; Kaur, Amanpreet; Qu, Guangzhi; Shaska, TonyThe growing market competition between the automakers led to the implementation of more entertainment systems and extra features to satisfy the automotive customers. The entertainment systems depend on wireless services and communication which led to increasing numbers of antennas mounted on and inside the vehicles. This dissertation is focused on automotive antenna design and the effect of the vehicle environment on the antenna performance. For the first part of the dissertation, a compact multi-band monopole antenna is designed for vehicular roof top shark-fin applications. The proposed multi-band antenna covers 5G sub-6GHz, GNSS and V2X frequency bands starting at 617MHz to 5925MHz. The presented antenna is a three-dimensional monopole antenna with two branches to cover the required bands with compact size to fit inside a roof top shark-fin. The antenna is simulated, optimized and then a prototype is fabricated, and its radiation characteristics are measured when mounted on one-meter ground plane and on a vehicle's roof. For the second part of the dissertation, the analysis of a C-V2X quarter-wavelength monopole antenna performance when mounted on a vehicle's glass roof is presented. Antenna gain measurements performed on a full glass roof exhibited a performance degradation in a linear average gain of 8 dB compared to when the same antenna is mounted on a metallic ground plane. In addition, the antenna radiation pattern on the glass roof had deep nulls. The antenna was simulated using a full-wave, three-dimensional electromagnetic field solver on the full glass sample with low emissivity (low-E) coating on the edges of the full glass roof and the simulation results showed acceptable agreement with the measurements. Simulation shows that the C-V2X antenna performance on the full glass roof can be improved by moving the low-E coating from underneath the glass to top of the glassItem NOVEL AUTOMOTIVE ANTENNA DESIGNS UTILIZING CHARACTERISTIC MODE ANALYSIS(2023-01-01) Abdul-Rahman, Ehab Mahmoud; Aloi, Daniel N; Li, Jia; Nassar, Sayed; Schmidt, DarrellThe Theory of Characteristic Modes (TCM) provides a valuable method for antenna analysis. It helps decompose the total radiation into a set of orthogonal radiation modes. Each mode exhibits a unique reaction in terms of its current distribution and radiation pattern. TCM has proven helpful in numerous antenna design applications, such as enhancing radiation patterns, decoupling antennas, increasing bandwidth, and achieving input impedance match.This study aims to apply characteristic mode analysis (CMA) to address automotive antenna design challenges. The work involves synthesizing and controlling the desired radiation characteristic mode (CM) at the intended frequency range to achieve an excellent radiation pattern for automotive applications. The study focuses on practical antenna design for the newly defined 5G-sub 6GHz cellular bands in the 0.617-5 GHz range and its cooperation with other coexisting wireless antennas for other wireless functions.Item SELF-CALIBRATING FUSION OF MULTI-SENSOR SYSTEM FOR AUTONOMOUS VEHICLE OBSTACLE DETECTION AND TRACKING(2023-01-01) Tian, Kaiqiao; Cheok, Ka C.; Mirza, Khalid; Radovnikovich, Micho Tomislav; Louie, Wing-Yue Geoffrey; Cesmelioglu, AycilMobile robots have gained significant attention due to their ability to undertake complex tasks in various applications, ranging from autonomous vehicles to robotics and augmented reality. To achieve safe and efficient navigation, these robots rely on sensor data from RADAR, LiDAR, and Cameras to understand their surroundings. However, the integration of data from these sensors presents challenges, including data inconsistencies and sensor limitations. This thesis proposes a novel LiDAR and Camera sensor fusion algorithm that addresses these challenges, enabling more accurate and reliable perception for mobile robots and autonomous vehicles. The proposed algorithm leverages the unique strengths of both LiDAR and camera sensors to create a holistic representation of the environment. It adopts a multi-sensor data fusion (MSDF) approach, combining the complementary characteristics of LiDAR's precise 3D Point Cloud Data and the rich visual information provided by cameras. The fusion process involves sensor data registration, calibration, and synchronization, ensuring accurate alignment and temporal coherence. The algorithm introduces a robust data association technique that mateches LiDAR points with visual features extracted from camera images. By fusing these data, the algorithm enhances object detection and recognition capabilities, enabling the robot to perceive the environment with higher accuracy and efficiency. Additionally, the fusion technique compensates for sensor-specific limitations, such as LiDAR's susceptibility to adverse weather conditions and the camera's vulnerability to lighting changes, resulting in a more reliable perception system. The thesis contributes to advancing mobile robot perception by providing a comprehensive and practical LiDAR and camera sensor fusion algorithm. This novel approach has significant implications for autonomous vehicles, robotics, and augmented reality applications, where accurate and reliable perception is vital for successful navigation and task execution. By addressing the limitations of individual sensors and offering a more unified and coherent perception system, the proposed algorithm paves the way for safer, more efficient, and intelligent mobile robot solutions in various real-world settings.Item Determining Spatial Relevancy of Objects for Improved Development of Multi-Object Tracking in Autonomous Driving Systems(2023-01-01) Hammod, Maen; Rawashdeh, Osamah; Lipták, László; Dean, Brian; Qu, GuangzhiThe perception system for autonomous vehicles (AVs) typically outputs all the objects it can observe in a scene. This is significantly more objects than what the AV would interact with, and far more than any human driver focus on during a driving task. Validating the perception system on all the observed objects could penalize its performance based on objects that will never interact with the AV or affect its planned trajectory. This dissertation outlines a strategy for identifying a subset of objects, referred to as Spatially Relevant Objects (SRO), that the perception system must perform exceptionally well on. This is valuable for several reasons and has many applications. For example, it can be used to determine the set of objects that should be included in the verification dataset for the perception system and thereby have a more efficient development cycle. Additionally, when evaluating the perception system on the SRO subset, the computed metrics not only evaluate the performance but also consider the real-world safety of the perception system, and the results would heavily support the safety case arguments. Finally, determining spatially relevant objects using a representative dataset then plotting their footprints relative to the AV can help determine and confirm the necessary sensing requirements and field of view coverage by prioritizing areas where SROs are most likely to appear. This is done without ignoring the fact that the world contains objects of different classes with different kinematics and could behave in a non-compliant way. The preliminary finding of applying our system showed that we can measure the performance of the perception system using a subset that averages about 11 of the observed objects without compromising the safety of the AV.Item Modeling and Control of Heat Transfer in a Single Vertical Ground Heat Exchanger for a Geothermal Heat Pump System(2023-01-01) Salhein, Khaled Asharef Assudani; Zohdy, Mohamed A; Kobus, Christopher J; Aloi, Daniel N; Olawoyin, Richard; Schmidt, Darrell PThe Ground Heat Exchanger (GHE) is regarded as the most critical component of a Geothermal Heat Pump System (GHPS) due to its direct contact with the Earth and ability to benefit from its relatively steady temperature. A GHE can attain the maximum benefit from the Earths heat when the water temperature reaches the ground, which occurs when the water velocity is moderate, allowing the heat exchanger to balance. Optimally, controlling water velocity is crucial such that the water reaches the desired temperature. Therefore, in this dissertation, I proposed a novel mathematical model of heat transfer behavior between the water inside the underground pipe and the surrounding ground for heating and cooling modes in a GHE. The proposed dynamic model was applied to three case studies of GHPS at Oakland University, the University Politècnica de València, and Oklahoma State University in heating and cooling modes to assess its validity and further enhance the performance of the GHE by determining the optimum velocity range. The results revealed the optimal water velocity ranges for three GHPSs. Model Predictive Control (MPC) was designed to optimize the GHE’s output temperature by controlling the water velocity, which can reduce the power consumption used for the water circulation pump and therefore maximize efficiency. In this dissertation, I also introduced an Improved Grey Prediction Model (IGM (1,1)). The proposed IGM (1,1) model was based on optimizing the current predicted value by subtracting the error prediction between the previous accumulated time response of the GM (1,1) model and the previous background value throughout the prediction length. The IGM (1,1) model was applied to perform the GHPS’s output temperature prediction eight hours in advance at Oklahoma State University, the University Politècnica de València, and Oakland University, respectively. Thus, the IGM (1,1) model outperformed the traditional GM (1,1) model for all used datasets.Item Innovative Designs For Low Profile Antenna Systems For Mimo 5G/V2X And Gnss Communications(2022-11-07) Yacoub, Ahmad; Aloi, Daniel N; Cesmelioglu, Aycil; Li, Jia; Qu, GuangzhiThe research in this dissertation shows the analysis and development of designing antenna elements and MIMO antenna systems that can be implemented in the automotive industry and have a significant role in an autonomous driving system. The antennas presented in this research cover 5G-sub-6GHz bands which have much more extended bandwidth compared to previous LTE network, in addition to covering Vehicle-to-Everything (V2X) frequency band. The design work presented in this research followed a scientific method that included simulating the antenna element using 3-D electromagnetic solver (HFSS) on 1-meter ground plane. The antenna was then fabricated using properlycut metal sheet, measured on 1-meter rolled-edge ground plane, and measured on a vehicle’s roof inside an anechoic chamber for practical measurements. The design guidelines and measurements are discussed in detail throughout this work. The first two sections of this research begin with presenting a novel wideband low-profile Planar Inverted F-Antenna (PIFA) that covers a wide frequency range (617MHz-6000MHz) that includes cellular 5G bands and V2X band while having reasonable rejection for Global Navigation Satellite System (GNSS) frequency bands. Then, Multiple MIMO configurations based on the novel PIFA design are studied by using spatial diversity, rotational diversity, and orthogonal diversity to increase the total throughput and data rate of the system. The performance of each element in the MIMO system is analyzed and discussed to evaluate the functionality of the system. The third section of this work introduces a 2x2 MIMO antenna system for vehicular application in the sub-6GHz 5G systems that operates in the middle and high frequency bands from 1.71GHz to 5GHz. The design consists of two novel raised printed monopoles on Flame Retardant 4 (FR4) dielectric material with Partial Ground Plane (PGP) structure to improve bandwidth impedance and achieve higher isolation across the operating frequency range. The design is an excellent candidate to be implemented in a shark-fin housing due to its low-profile characteristics and good electrical performance. Eventually, in the fourth section of this work, a fully integrated low-profile antenna systems for MIMO 5G and global navigation satellite system (GNSS) for L1/L5 frequency bands is presented. The designs can be used on the vehicle’s roof inside a low profile housing due to its physical parameters and RF performance.Item Investigations Of Magnetic/Electric Field Control Of Magnetization Of Ferromagnetic And Multiferroics(2022-11-09) Xiong, Yuzan; Qu, Hongwei; Zhang, Wei; Li, Jia; Yang, Ankun; Shillor, MeirThe shortcomings of contemporary complementary metal oxide semiconductor (CMOS) technologies include increased power consumption, scalability, volatility, and device variability. New materials and novel devices are being investigated in this regard. Spintronic devices, which are normally based on magnetic materials, store and process data based on the modes of electron spins, rather than the presence or absence of charges as in the CMOS, are one possible approach. Numerous potential advantages of spintronic devices include its quick operational speed, low power requirement, and non-volatility. Two ferromagnetic materials suitable for creating spintronic devices are investigated in his dissertation study. Material properties, techniques for regulating the magnetization of materials, with both magnetic and electrical fields, and the development of devices useful for use in frequency modulations are all respectively detailed.The first section of this dissertation studies the magnetically-induced transparence (MIT) effect in Y3Fe5O12 (YIG)/Permalloy (Py) coupled bilayers. The measurement is achieved via a heterodyne detection of the coupled magnetization dynamics using a single wavelength that probes the magneto-optical Kerr and Faraday effects of Py and YIG, respectively. Clear features of the MIT effect are evident from the deeply modulated ferromagnetic resonance of Py due to the perpendicular-standing-spin-wave of YIG. We develop a phenomenological model that nicely represents the experimental results including the induced amplitude and phase evolution caused by the magnon-magnon coupling. This work offers a new route towards studying phase-resolved spin dynamics and hybrid magnonic systems. The second part of this dissertation discusses the research on the hexaferrite material, Zn2Y, and the prospect of controlling its magnetic characteristics by applying a dc voltage, which is akin to a bias electric field. The detection and investigation of the magnetoelectric (ME) effect for in-plane currents orthogonal to the hexagonal axis in single crystal and thin films of Zn2Y grown via liquid phase epitaxy. By applying a dc voltage, tuning of ferromagnetic resonance (FMR) was achieved in the hexaferrites. In addition to the frequency shift caused by the electrical tuning, magnetic properties of the material as a function of the input tuning power was also studied.Item Robust Non-Linear Lyapunov Deep Learning Control Design For Chaotic Systems(2022-11-07) Mahmoud, Amr Salah; Zohdy, Mohamed; Dean, Brian; Schmidt, Darrell; Olawoyin, RichardDespite their operational success, machine learning controllers lack theoretical guarantees in terms of system stability. In contrast, classic model-based controller design uses principled approaches such as Linear Quadratic Regulator (LQR) to synthesize stable controllers with verifiable proofs. In addition, deep learning controllers encounter feedback timing bottlenecks that increase exponentially with the system complexity. Deep learning is also dependent on the quality and diversity of the dataset to produce unbiased findings; therefore, the prediction of deep learning is not guaranteed. As a result, in this research, we develop and implement a guaranteed stability solution for safety critical and chaotic systems through the integration of Lyapunov Stability theory and deep machine learning. Three control methods are researched, leading to the development of the Deep Lyapunov-stable controller: the deep learning methodology, the Lyapunov control function, and controller parameters. In this research, we provide a generic method for synthesizing a Deep Lyapunov-stable control and a way to simultaneously confirm its stability. A unique Lyapunov control function is devised and shown to be effective in managing Duffing, Van der Pol, and Zohdy-Harb nonlinear systems, but with restrictions on the system's oscillation frequency, initial conditions and disturbances. Subsequently, Dynamic Lyapunov Deep Learning is introduced to alleviate the Lyapunov control’s shortcomings. Developing a deep learning architecture in combination with a customized Lyapunov control resolves the temporal delay and Lyapunov parameters calibration concern. Different datasets are also presented before establishing the one with the best accuracy. In addition to the dataset, the architecture of the deep learning model has a significant effect on the model's accuracy. A process for relearning is intended to accommodate the introduction of new system dynamics. Based on the correlation study, we also designed an optimization technique to improve the integration of the deep learning layer and controller layer. The proposed integration of Deep Learning and Lyapunov Control, referred to as Lyapunov Deep Learning (LDL) control, is applied in MATLAB / SIMULINK to the magnetic levitation chaotic nonlinear system to demonstrate its effectiveness in addressing sudden changes in system behavior, the environment, and demands in comparison to other methods of control.