In Radio Frequency (RF) integrated circuit design field, programmable dividers are getting more and more attentions in recent years. A programmable frequency divider can divide an input frequency by programmable ratios [1]. It is a key component of a frequency synthesizer. It also can be used to generate variable clock-signals for: switched-capacitor filters (SCFs), digital systems with different power-states, as well as multiple clock-signals on the same system-on-a-chip (SOC). These circuits need high performance programmable frequency dividers, operating at high frequencies and having wide division ratio ranges, with binary division ratio controls and 50% output duty-cycle. Different types of programmable frequency dividers are reviewed and compared. A programmable frequency divider with a wide division ratio range of (8 ~ 524287) has been reported [2]. Because the output duty-cycle of this reported divider is far from 50%, the circuit in [2] has very limited applications. The proposed design solves this problem, without compromising other advantages of the design in [2]. The proposed design is fabricated in a 0.18-μm RF CMOS process. Test results show that the output duty-cycle is 50% when the division ratio is an even number. The duty-cycle is 44.4% when the division ratio is 9. The output duty-cycle becomes closer to 50% when the division ratio is an increasing odd number. For each division ratio, the output duty-cycle remains constant, with different input frequencies from GHz down to kHz ranges, with different temperatures and power supply voltages. This thesis provides an explanation of the design details and test results. A Phase Locked-Loop (PLL) based frequency synthesizer can generate different output frequencies. A programmable frequency divider is an important component of this type of PLL. Since bandwidth is expensive, it is preferred to reduce the frequency channel distance of a frequency synthesizer. Using a fractional programmable divider, the frequency channel distance of a PLL can be reduced, without reducing the reference frequency or increasing the settling time of the PLL. A frequency synthesizer with a programmable fractional divider is designed and fabricated. A brief description of the PLL design and test results are presented in this dissertation.

As the development of Silicon (Si) semiconductor technology slows down due to its material limitations, more and more attention is being paid to wide bandgap material based semiconductor technology. Silicon Carbide (SiC) has been widely recognized as the material for next generation power electronic devices. However, a great deal of work needs to be done before SiC power devices can be widely applied. This dissertation addresses this need and has conducted research on the modeling of SiC power electronic system. More specifically, a method for system modeling of a SiC power system based on basic physics and device tests is presented here. It includes temperature-dependent single device models specified for system-level modeling, power loss models for power converters and thermal models for cooling system. The method is verified by experimental results. Furthermore, it is used to study the system impact of SiC power devices in several different applications, which were funded by Small Business Innovation Research (SBIR) and Oak Ridge National Laboratory (ORNL). A conclusion is drawn from these studies that SiC power devices are more suitable for high-power, high-temperature, and high-frequency systems compared to Si ones. Thus, these kinds of systems will be the potential applications of SiC power devices in the near future.

This thesis is concerned with modeling of both space and time variations of Ultra Wide Band (UWB) indoor channels. The most common empirically determined amplitude distribution in many UWB environments is Nakagami distribution. The latter is generalized to stochastic diffusion processes which capture the dynamics of UWB channels. In contrast with the traditional models, the statistics of the proposed models are shown to be time varying, but converge in steady state to their static counterparts. System identification algorithms are used to extract various channel parameters using received signal measurement data, which are usually available at the receiver. The expectation maximization (EM) algorithm and the Kalman filter (KF) are employed in estimating channel parameters as well as the inphase and quadrature components, respectively. The proposed algorithms are recursive and therefore can be implemented in real time. Further, sufficient conditions for the convergence of the EM algorithm are provided. Comparison with recursive Least-square (LS) algorithms is carried out using experimental measurements. Distributed stochastic power control algorithms based on the fixed point theorem and stochastic approximations are used to solve for the optimal transmit power problem and numerical results are also presented. A framework which can capture the statistics of the overall received signal and a methodology to estimate parameters of the counting process based on the received signal is developed. Furthermore, second moment statistics and characteristic functions are computed explicitly and considered as an extension of Rice’s shot noise analysis. Another two important components, input design and model selection are also considered. Gel’fand n-widths and Time n-widths are used to represent the inherent error introduced by input design. Kolmogorov n-width is used to characterize the representation error introduced by model selection. In particular, it is shown that the optimal model for reducing the representation error is a finite impulse response (FIR) model and the optimal input is an impulse at the start of the observation interval.

Throughout the years Hybrid Electric Vehicles (HEV) require an electric motor which has high power density, high efficiency, and wide constant power operating region as well as low manufacturing cost. For these purposes, a new Interior Permanent Magnet Synchronous Motor (IPMSM) with brushless field excitation (BFE) is designed and analyzed. This unique BFE structure is devised to control the amount of the air-gap flux for the purpose of achieving higher torque by increasing the air-gap flux at low speed and wider operating speed range by weakening the flux at high speed. On the process of developing the new IPMSM, the following analysis results are presented. Firstly, a new analytical method of output torque calculations for IPMSM is shown. This method works well when using a 2-dimensional magnetic equivalent circuit of a machine by omitting the step of calculating the inductance values which are required for the calculation of the reluctance torque. Secondly, there is a research about the slanted air-gap shape. This structure is intended to maximize the ratio of the back-emf of a machine that is controllable by BFE as well as increase the output torque. The study of various slanted air-gap shapes suggests a new method to increase torque density of IPMSM. Lastly, the conventional two-axis IPMSM model is modified to include the cross saturation effect by adding the cross-coupled inductance terms for calculating the power factor and output torque in comparing different saturated conditions. The results suggest that the effect of cross-coupled inductance is increase when d-axis current is high on the negative direction.

Today many efforts are made to research and use new energy sources because the potential for an energy crisis is increasing. Multilevel converters have gained much attention in the area of energy distribution and control due to its advantages in high power applications with low harmonics. They not only achieve high power ratings, but also enable the use of renewable energy sources. The general function of the multilevel converter is to synthesize a desired high voltage from several levels of dc voltages that can be batteries, fuel cells, etc. This dissertation presents a new hybrid multilevel inverter for voltage boost. The inverter consists of a standard 3-leg inverter (one leg for each phase) and H-bridge in series with each inverter leg. It can use only a single DC power source to supply a standard 3-leg inverter along with three full H-bridges supplied by capacitors or batteries. The proposed inverter could be applied in hybrid electric vehicles (HEVs) and fuel cell based hybrid electric vehicles (FCVs). It is of voltage boosting capability and eliminates the magnetics. This feature makes it suitable for the motor running from low to high power mode. In addition to hybrid electric vehicle applications, this paper also presents an application where the hybrid multilevel inverter acts as a renewable energy utility interface. In this dissertation, the structure, operation principle, and modulation control schemes of the proposed hybrid multilevel inverter are introduced. Simulation models and results are described and analyzed. An experimental 5 kW prototype inverter is built and tested.

Cellular functions are controlled by genetic regulatory networks called gene circuits. Recently, there has been much interest in how gene circuits deal with or even exploit stochastic fluctuations in molecular species within the cellular environment. Through a coupling of analysis and simulation with experimentation, this dissertation work furthers the understanding of gene circuit noise behavior and makes significant contributions to the analytical and experimental tools that are currently available for the study and design of natural and synthetic gene circuits. In this study, models are developed for unregulated and autoregulated gene circuits. Results from the analysis are compared to computer simulations and experimental results. Exact stochastic simulations show that the derived analytical expressions are valid even for populations as low as 10 molecules, despite linear approximations made by the analysis. The experimental portion of this work presents a novel method for acquiring in vivo measurements of real-time gene expression. The techniques developed here are used to report the very first measurements of frequency content in gene circuit noise and verify theoretical predictions that negatively autoregulated gene circuits shift their noise spectra up to higher frequency. Through measured shifts in noise spectra, these frequency measurements can also reveal subtle and condition-dependent regulatory pathways. Measured noise spectra may also permit in vivo estimation of gene circuit kinetic rate parameters.

This dissertation addresses automated surveillance systems focusing on four topics: (1) spatial mappings of omnidirectional and PTZ cameras, and PTZ and PTZ cameras; (2) target hopping application for dual camera systems; (3) camera handoff and placement; (4) the mobile tracking platform. The four topics represent four contributions in this dissertation. Dual camera systems have been widely used in surveillance because of the ability to explore the wide field of view (FOV) of the omnidirectional camera and the wide zoom range of the PTZ camera. Most existing algorithms require a priori knowledge of the projection models of omnidirectional and PTZ cameras to solve the spatial mapping between any two cameras. The proposed methods not only improve the mapping accuracy by reducing the dependence on the knowledge of the projection model but also improved flexibility in adjusting to varying system configurations. The omnidirectional camera is capable of multi object tracking while the PTZ camera is able to track one individual target at one time to maintain the required resolution. It becomes necessary for the PTZ camera to distribute its observation time among multiple objects and visit them in sequence. In comparison with the sequential visiting and nearest neighbor methods, the proposed adaptive algorithm requires less computational and visiting time. Tracking with multiple cameras is mainly the consistent labeling or camera handoff problem. An automatic calibration procedure combined with Wilcoxon Signed-Rank Test is proposed to solve the consistent labeling problem. Meanwhile, we introduce an additional constraint to search for optimal cameras‘ overlapped field of views (FOVs) and resource management approach to improve camera handoff performance. Experiments show that our proposed camera handoff and placement can outperform existing approaches. However, in the majority of surveillance systems, their cameras are stationary. These stationary systems often require the desired object to stay within the surveillance range of the system. Thus, the robotic platform we propose uses a visual camera to sense the movement of the desired object and a range sensor to help the robot detect and then avoid obstacles in real time while continuing to track and follow the desired object. Experiment shows this robotic and intelligent system can fulfill the requirements of tracking an object and avoiding obstacles simultaneously when the object moves in speed of 4 km/hr.

Multi-channel analog to digital converters (ADCs) are required where signals from multiple sensors can be digitized. A lower power per channel for such systems is important in order that when the number of channels is increased the power does not increase drastically. Many applications require signals from current output sensors, such as photosensors and photodiodes to be digitized. Applications for these sensors include spectroscopy and imaging. The ability to digitize current signals without converting currents to voltages saves power, area, and the design time required to implement I-to-V converters. This work describes a novel and unique current-mode multi-channel integrating ADC which processes current signals from sensors and converts it to digital format. The ADC facilitates the processing of current analog signals without the use of transconductors. An attempt has been made also to incorporate voltage-mode techniques into the current-mode design so that the advantages of both techniques can be utilized to augment the performance of the system. Additionally since input signals are in the form of currents, the dynamic range of the ADC is less dependant on the supply voltage. A prototype 4-channel ADC design was fabricated in a 0.5-micron bulk CMOS process. The measurement results for a 10Ksps sampling rate include a DNL, which is less than 0.5 LSB, and a power consumption of less than 2mW per channel.

The rising cost of gasoline and environmental concerns have heightened the interest in electric/hybrid-electric vehicles. In passenger vehicles an electric traction motor drive must achieve a constant power speed range (CPSR) of about 4 to 1. This modest requirement can generally be met by using most of the common types of electric motors. Heavy electric vehicles, such as tanks, buses and off-road equipment can require a CPSR of 10 to 1 and sometimes much more. Meeting the CPSR requirement for heavy electric vehicles is a significant challenge. This research addresses the CPSR capability and control requirements of two candidates for high CPSR traction drives: the permanent magnet synchronous motor (PMSM) and the switched reluctance motor (SRM). It is shown that a PMSM with sufficiently large winding inductance has an infinite CPSR capability, and can be controlled using a simple speed control loop that does not require measurement of motor phase currents. Analytical and experimental results confirm that the conventional phase advancement method charges motor winding with required current to produce the rated power for the speed range where the back-EMF normally prevents the generation of the rated power. A key result is that for the PMSM, the motor current at high speed approaches the machine rating independent of the power produced. This results in poor partial load efficiency. The SRM is also shown to have infinite CPSR capability when continuous conduction is permitted during high speed operation. Traditional high speed control is of discontinuous type. It has been shown that this discontinuous conduction itself is the limiter of CPSR. Mathematical formulas have been developed relating the average current, average power, and peak current required producing the desired (rated) power to machine design parameters and control variables. Control of the SRM in the continuous conduction mode is shown to be simple; however, it does require measurement of motor current. For the SRM the motor current at high speed is proportional to the power produced which maintains drive efficiency even at light load conditions.

A fault diagnostic and reconfiguration system in a multilevel inverter drive (MLID) using artificial intelligent based techniques is developed in this dissertation. Output phase voltages of a MLID can be used as valuable information to diagnose faults and their locations. It is difficult to diagnose a MLID system using a mathematical model because MLID systems consist of many switching devices and their system complexity has a nonlinear factor. Therefore, a neural network (NN) classification is applied to the fault diagnosis of a MLID system. Multilayer perceptron (MLP) networks are used to identify the type and location of occurring faults. The principal component analysis (PCA) is utilized in the feature extraction process to reduce the NN input size. A lower dimensional input space will also usually reduce the time necessary to train a NN, and the reduced noise may improve the mapping performance. The genetic algorithm is also applied to select the valuable principal components. The comparison among MLP neural network (NN), principal component neural network (PC-NN), and genetic algorithm based selective principal component neural network (PC-GA-NN) are performed. Proposed neural networks are evaluated with simulation test set and experimental test set. The PC-NN has improved overall classification performance from NN by about 5% points, whereas PC-GA-NN has better overall classification performance from NN by about 7.5% points. Therefore, the application of a genetic algorithm improves the classification from PC-NN by about 2.5% point. The overall classification performance of the proposed networks is more than 90%. A reconfiguration technique is also developed. The effects of using the developed reconfiguration technique at high modulation index are addressed. The developed fault diagnostic system is validated with experimental results. The developed fault diagnostic system requires about 6 cycles at 60 Hz to clear an open circuit and about 9 cycles at 60 Hz to clear a short circuit fault. The experimental results show that the developed system performs satisfactorily to detect the fault type, fault location, and reconfiguration.