Since its invention, phased array has been extensively applied in both military and civil areas. The applications include target detecting and tracking, space probe communication, broadcasting, human-machine interfaces, and remote sensing. Although the phased array applications show a broad range of potential market, there are some limitations of phased array's development: high cost, complex structure, narrow bandwidth, and high power consumption. Therefore, novel ideas are needed to reduce these constraints. In this thesis, several new approaches about the design and application of phased array are presents. First, the principle of phased array and fundamental design equations are introduced. Second, a new application of phased array antenna for radar respiration measurement is presented. By integrating a 4×4 Butler matrix with four-element antenna array, there will be four distinct main beams in radiation pattern. This new approach can improve the measurement accuracy and realize a high detecting rate. Third, a compact phased array antenna system based on dual-band operations is introduced. Dual-band function can make N-antenna system obtain 2N unique radiation beams (N is an integer) and achieve a significant size reduction compared to the conventional single-band system. To verify the design concept, a four-element phased array antenna working at 5GHz and …

In this thesis, I present my work on the modeling and control of a motor system using the Lego EV3 robot. The overall goal is to apply introductory systems and controls engineering techniques for estimation and design to a real-world system. First I detail the setup of materials used in this research: the hardware used was the Lego EV3 robot; the software used was the Student 2014 version of Simulink; a wireless network was used to communicate between them using a Netgear WNA1100 wifi dongle. Next I explain the approaches used to model the robot’s motor system: from a description of the basic system components, to data collection through experimentation with a proportionally controlled feedback loop, to parameter estimation (through time-domain specification relationships, Matlab’s curve-fitting toolbox, and a formal least-squares parameter estimation), to the discovery of the effects of frictional disturbance and saturation, and finally to the selection and verification of the final model through comparisons of simulated step responses of the estimated models to the actual time response of the motor system. Next I explore three different types of controllers for use within the motor system: a proportional controller, a lead compensator, and a PID controller. I catalogue the …

Water scarcity for agriculture is one of the most important challenges to improve food security worldwide. In this thesis we study the potential to develop a low-cost controller for a small scale brackish desalination plant that consists of proven water treatment technologies, reverse osmosis, cation exchange, and nanofiltration to treat groundwater into two final products: drinking water and irrigation water. The plant is powered by a combination of wind and solar power systems. The low-cost controller uses Arduino Mega, and Arduino DUE, which consist of ATmega2560 and Atmel SAM3X8E ARM Cortex-M3 CPU microcontrollers. These are widely used systems characterized for good performance and low cost. However, Arduino also requires drivers and interfaces to allow the control and monitoring of sensors and actuators. The thesis explains the process, as well as the hardware and software implemented.

The thesis implements a vision-based leader-follower tracking algorithm on a ground robot system. One camera is the only sensor installed the leader-follower system and is mounted on the follower. One sphere is the only feature installed on the leader. The camera identifies the sphere in the openCV Library and calculates the relative position between the follower and leader using the area and position of the sphere in the camera frame. A P controller for the follower and a P controller for the camera heading are built. The vision-based leader-follower tracking algorithm is verified according to the simulation and implementation.

This thesis dissertation mainly compares and investigates laboratory study of different implementation methodologies of applied control systems and how they can be adopted in industrial, as well as commercial, automation applications. Namely the research paper aims to assess or evaluate eventual feedback control loops' performance and robustness over multiple conventional or state-of-the-art technologies in the field of applied industrial automation and instrumentation by implementing a laboratory case study setup: the ball on beam system. Hence, the paper tries to close the gap between industry and academia by: first, conducting a historical study and background information of main evolutional and technological eras in the field of industrial process control automation and instrumentation. Then, some related basic theoretical as well as practical concepts are reviewed in Chapter 2 of the report before displaying the detailed design. After that, the next Chapter, analyses the ball on beam control system problem as the case studied in the context of this research through reviewing previous literature, modeling and simulation. The following Chapter details the proposed design and implementation of the ball on beam case study as if it is under the introduced distributed industrial automation architecture. Finally, Chapter 5 concludes this work by listing several …

This paper describes a procedure to find the transfer function for the Lego Mindstorms Ev3. Lego Mindstorms Ev3 can serve as the platform for a system modeling and a controller design course. It is economical and accessible. It is also very compatible with Matlab and Simulink. This platform can be used for concepts of modeling, feedback, and controller design. The main approach in this work focuses on the closed loop instead of open loop. Although this approach turns the problem into a more complicated puzzle, it reveals more details. In this work, different techniques have been used, such as time domain, root locus, and least square estimation. Different tools have also been utilized such as Matlab SISO tool, the Matlab System Identification tool, and Simulink. These methods and implementations assisted to acquire different types of transfer functions for the system. By simulating the transfer functions and comparing them with experimental studies, the matching scores were calculated to decide on the best transfer function. Finding the finest transfer function for this gadget enables us to prepare diverse practical undergraduate and graduate curricula.

More than 80% of the people in urban regions and about 98% of cities in low and middle income countries have poor air quality according to the World Health Organization. People living in such environment suffer from many disorders like a headache, shortness of breath or even the worst diseases like lung cancer, asthma etc. The main objective of the thesis is to create awareness about the air quality and the factors that are causing air pollution to the people which is really important and provide tools at their convenience to measure and analyze the air quality. Taking real time air quality scenarios, various experiments were made using efficient sensors to study both the indoor and outdoor air quality. These experimental results will eventually help people to understand air quality better. An outdoor air quality data measurement system is developed in this research using Python programming to provide people an opportunity to retrieve and manage the air quality data and get the concentrations of the leading pollutants. The entire designing of the program is made to run with the help of a graphical user interface tool for the user, as user convenience is considered as one of the objectives of …

Allocation of expensive resources, (such as Multiplier) onto the CGRA has been of interest from quite some time. For these architectural solutions to fulfill the designers' requirements, it is of utmost importance that the design offers high performance, low power consumption, and effective area utilization. The allocation problem is studied using the UntangledII gaming environment, which has been developed at the Reconfigurable Computing Lab at UNT to discover the design of custom domain-specific architectures. This thesis explores several case-studies to investigate the arrangement of functional units and interconnects to achieve a low power, high performance, and flexible heterogeneous designs that can fit for a suite of applications. In the later part, several human mapping strategies of top and bottom players to design a custom domain-specific architecture are presented. Some common trends that were examined while analyzing the mapping strategies of the players are also discussed.

Low-density parity check (LDPC) codes are very popular among error correction codes because of their high-performance capacity. Numerous investigations have been carried out to analyze the performance and simplify the implementation of LDPC codes. Relatively slow convergence of iterative decoding algorithm affects the performance of LDPC codes. Faster convergence can be achieved by reducing the number of iterations during the decoding process. In this thesis, a new approach for faster convergence is suggested by choosing a systematic parity check matrix that yields lowest Second Smallest Eigenvalue Modulus (SSEM) of its corresponding Laplacian matrix. MATLAB simulations are used to study the impact of eigenvalues on the number of iterations of the LDPC decoder. It is found that for a given (n, k) LDPC code, a parity check matrix with lowest SSEM converges quickly as compared to the parity check matrix with high SSEM. In other words, a densely connected graph that represents the parity check matrix takes more iterations to converge than a sparsely connected graph.

Formation control is a classical problem and has been a prime topic of interest among the scientific community in the past few years. Although a vast amount of literature exists in this field, there are still many open questions that require an in-depth understanding and a new perspective. This thesis contributes towards exploring the wide dimensions of formation control and implementing a formation control scheme for a group of multi-agent systems. These systems are autonomous in nature and are represented by double integrated dynamics. It is assumed that the agents are connected in an undirected graph and use a leader-follower architecture to reach formation when the leading agent is given a velocity that is piecewise constant. A MATLAB code is written for the implementation of formation and the consensus-based control laws are verified. Understanding the effects on formation due to a fixed formation geometry is also observed and reported. Also, a link that describes the functional similarity between desired formation geometry and the Laplacian matrix has been observed. The use of Laplacian matrix in stability analysis of the formation is of special interest.

In this thesis the general Chebyshev filter synthesis procedure to generate transfer and reflection polynomials and coupling matrices were described. Key concepts such as coupled resonators, non-resonant nodes have been included. This is followed by microwave duplexer synthesis. Next, a technique to design dual band filter has been described including ways to achieve desired return loss and rejection levels at specific bands by manipulating the stopbands and transmission zeros. The concept of dual band filter synthesis has been applied on the synthesis of microwave duplexer to propose a method to synthesize dual band duplexers. Finally a numerical procedure using Cauchy method has been described to estimate the filter and duplexer polynomials from measured responses. The concepts in this thesis can be used to make microwave filters and duplexers more compact, efficient and cost effective.

Modern machine learning techniques focus on extremely deep and multi-pathed networks, resulting in large memory and computational requirements. This thesis explores techniques for designing efficient convolutional networks including pixel shuffling, depthwise convolutions, and various activation fucntions. These techniques are then applied to two image processing domains: single-image super-resolution and image compression. The super-resolution model, TinyPSSR, is one-third the size of the next smallest model in literature while performing similar to or better than other larger models on representative test sets. The efficient deep image compression model is significantly smaller than any other model in literature and performs similarly in both computational cost and reconstruction quality to the JPEG standard.

A modified, single error-correcting, and double error detecting Hamming code, hereafter referred to as modified SEC-DED Hamming code, is proposed in this research. The code requires fewer logic gates to implement than the SEC-DED Hamming code. Also, unlike the popular Hsiao's code, the proposed code can determine the error in the received word from its syndrome location in the parity check matrix. A detailed analysis of the area and power utilization by the encoder and decoder circuits of the modified SEC-DED Hamming code is also discussed. Results demonstrate that this code is an excellent alternative to Hsiao's code as the area and power values are very similar. In addition, the ability to locate the error in the received word from its syndrome is also of particular interest. Primitive polynomials play a crucial role in the hardware realizations for error-correcting codes. This research describes an implementation of a scalable primitive polynomial circuit with coefficients in GF(2). The standard cell area and power values for various degrees of the circuit are analyzed. The physical design of a degree 6 primitive polynomial computation circuit is also provided. In addition to the codes, a background of the already existing SPX GCD computation algorithm is …

In the vast field of signal processing, machine learning is rapidly expanding its domain into all realms. As a constituent of this expansion, this thesis presents contributive work on advancements in machine learning algorithms by building on the shoulder of giants. The first chapter of this thesis contains enhancements to a CNN (convolutional neural network) for better classification of heartbeat arrhythmia. The network goes through a two stage development, the first being augmentations to the network and the second being the implementation of dropout. Chapter 2 involves the combination of CNN and LSTM (long short term memory) networks for the task of short-term energy use data regression. Exploiting the benefits of two of the most powerful neural networks, a unique, novel neural network is created to effectually predict future energy use. The final section concludes this work with directions for future works.

In this thesis, we conduct a preliminary study on the controller design for directional antenna devices carried by drones. The goal of the control system is to ensure the best alignment between two directional antennas so as to enhance the performance of air-to-air communication between the drones. The control system at the current stage relies on the information received from GPS devices. The control system includes two loops: velocity loop and position loop to suppress wind disturbances and to assure the alignment of two directional antennae. The simulation and animation of directional antennae alignment control for two-randomly moving drones was developed using SIMULINK. To facilitate RSSI-based antenna alignment control to be conducted in the future work, a study on initial scanning techniques is also included at the end of this thesis.

This thesis presents a new approach to extend and reduce the transmission range in wireless systems. Conditioning is defined as purposeful electromagnetic interference that affects a wireless signal as it propagates through the air. This interference can be used constructively to enhance a signal and increase its energy, or destructively to reduce energy. The constraints and limitations of the technology are described as a system model, and a flow chart is used to describe the circuit process. Remaining theoretical in nature, practical circuit implementations are foregone in the interest of elementary simulations depicting the interactions of modulated signals as they experience phase mismatch. Amplitude modulation and frequency modulation are explored with using both positive and negative conditioning, and conclusions to whether one is more suitable than the other are made.

Among various energy harvesting technologies reverse electrowetting-on-dielectric energy harvesting (REWOD) has been proved to harvest energy from low frequency motion such as many human motion activities (e.g. walking, running, jogging etc.). Voltage rectification and DC-DC boosting of low magnitude AC voltage from REWOD can be used to reliably self-power the wearable sensors. In this work, a commercial component-based rectifier and DC-DC converter is designed and experimentally verified, for further miniaturization standard 180 nm CMOS process is used to design the rectifier and the DC-DC boost converter.This work also includes the MATLAB based model for REWOD energy harvester for various REWOD models. In REWOD energy harvesting, a mechanical input during the motion causes the electrolyte placed in between two dissimilar electrodes to squeeze back and forth thereby periodically changing the effective interfacial area, hence generating alternating current. The alternating current is given to the rectifier design. There is no realistic model that has been developed yet for this technique. Thereby, a MATLAB based REWOD model is developed for the realistic simulation of the REWOD phenomenon. In the work, a comparison of different REWOD models such as planar surface, rough surface and porous models are performed demonstrating the variations in capacitance, current …

This dissertation focuses on the path planning of unmanned aerial vehicle (UAV) swarms under distributed and hybrid control scenarios. It presents two such models and analyzes them both from theory and practice. In the first method, a distributed formation control strategy for UAV swarm based on consensus law is presented. This model makes use of the fundamental concepts of leader-follower structure, social potential functions, and algebraic graph theory to jointly address flocking and de-confliction in the formation control problem. The impact of network topology on formation control is analyzed. It is shown that the degree distribution of the network representing the multi-agent system defines the rate at which formation is attained. Conditions for convergence and stability are derived. In the second method, a hybrid framework for path planning and coverage area by UAV swarms is presented. This strategy significantly improves the current labor-intensive and resource-constraint operations in aquaculture farms. To monitor the farms periodically, an optimized back-and-forth flight path based on the Shamos algorithm is utilized. A trajectory tracking strategy for UAV swarms under uncertain wind conditions is presented.

This thesis focuses on the recording challenges faced in biomedical systems. More specifically, the challenges in neural signal recording are explored. Instead of the typical synchronous ADC system, a level crossing ADC is detailed as it has gained recent interest for low-power biomedical systems. These systems take advantage of the time-sparse nature of the signals found in this application. A 10-bit design is presented to help capture the lower amplitude action potentials (APs) in neural signals. The design also achieves a full-scale bandwidth of 1.2 kHz, an ENOB of 9.81, a power consumption of 13.5 microwatts, operating at a supply voltage of 1.8 V. This design was simulated in Cadence using 180 nm CMOS technology.

In situations where information infrastructure is destroyed or not available, on-demand information infrastructure is pivotal for the success of rescue missions. In this paper, a drone-carried on-demand information infrastructure for long-distance WiFi transmission system is developed. It can be used in the areas including emergency response, public event, and battlefield. In years development, the Drone WIFI System has developed from single-CPU platform, twin-CPU platform, Atmega2560 platform to NVIDIA Jetson TX2 platform. By the upgrade of the platform, the hardware shows more and more reliable and higher performance which make the application of the platform more and more exciting. The latest TX2 platform can provide real time and thermal video transmission, also application of deep learning of object recognition and target tracing. All these up-to-date technology brings more application scenarios to the system. Therefore, the system can serve more people in more scenarios.

The new developments in coding theory research have revolutionized the application of coding to practical systems. Low-Density Parity Check (LDPC) codes form a class of Shannon limit approaching codes opted for digital communication systems that require high reliability. This thesis investigates the underlying relationship between the spectral properties of the parity check matrix and LDPC decoding convergence. The bit error rate of an LDPC code is plotted for the parity check matrix that has different Second Smallest Eigenvalue Modulus (SSEM) of its corresponding Laplacian matrix. It is found that for a given (n,k) LDPC code, large SSEM has better error floor performance than low SSEM. The value of SSEM decreases as the sparseness in a parity-check matrix is increased. It was also found from the simulation that long LDPC codes have better error floor performance than short codes. This thesis outlines an approach to analyze LDPC decoding based on the eigenvalue analysis of the corresponding parity check matrix.

In light of incidents and concerns regarding the vulnerability of the global positioning system (GPS), the main purpose of the thesis is to look at alternative systems for radio guidance and to put up a serious study on such alternatives with receive and transmit antenna. There is also the need to design such antennas with multiple frequencies to offer robustness in the unlikely event that such adversarial attacks on the GPS happen. The basis on which such alternative antennas are designed is a slotted microstrip. The characteristics of the slot or slots on the microstrip are analyzed by mapping their exact locations on the patch and then noting the resultant center frequencies, the return losses, and the bandwidth. The activities associated with this also focus on the design, fabrication, validation, and characterization of one or more slotted antennas prototypes. The measurement of the antenna prototypes does confirm several frequencies that coexist to see applications, in aeronautical radionavigation, fixed-mobile radionavigation, and radiolocation. The antennas could also feature in a wide-area augmentation system (WAAS), satellite ground link system (SGLS) as well as in surveillance and precision approach radars. Some variations of the antenna are deployed in the areas of law enforcement, surveillance, …

Integrated Circuits (ICs) have a broad range of applications in healthcare, military, consumer electronics etc. The acronym VLSI stands for Very Large Scale Integration and is a process of making ICs by placing millions of transistors on a single chip. Because of advancements in VLSI design technologies, ICs are getting smaller, faster in speed and more efficient, making personal devices handy, and with more features. In this thesis work an interactive framework is designed in which the fundamental concepts of digital logic design and VLSI design such as logic gates, MOS transistors, combinational and sequential logic circuits, and memory are presented in a simple, interactive and user friendly way to create interest in students towards engineering fields, especially Electrical Engineering and Computer Engineering. Most of the concepts are explained in this framework by taking the examples which we see in our daily lives. Some of the critical design concerns such as power and performance are presented in an interactive way to make sure that students can understand these significant concepts in an easy and user friendly way.

Noise-induced hearing loss is a serious problem common to musical environments. Current dosimetry technology is primarily designed for industrial environments and not suited for musical settings. At present, there are no government regulations that apply to the educational music environment as it relates to monitoring and prevention of hearing loss. Also, no system exists than can serve as a proactive tool in observation and reporting of sound exposure levels with the goal of hearing conservation. Newly proposed system takes a software based approach in designing a proactive dosimetry system that can assess the risk of sound noise exposure. It provides real-time feedback trough a graphical user interface that is capable of database storage for further study.