Electrical and Computer Engineering

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https://hdl.handle.net/10323/11889

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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, Aycil
Video 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.
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 Ali
Power 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.
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, Guangzhi
The 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.
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, Aycil
Mobile 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.
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 P
Electric 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.
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 P
Electric 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.
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 P
Electric 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.

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