A successful power system in military applications (warship, aircraft, armored vehicle etc.) must operate acceptably under a wide range of conditions involving different loading configurations; it must maintain war fighting ability and recover quickly and stably after being damaged. The introduction of energy storage for the power system of an electric warship integrated engineering plant (IEP) may increase the availability and survivability of the electrical power under these conditions. Herein, the problem of energy storage control is addressed in terms of maximizing the average performance. A notional medium-voltage dc system is used as the system model in the study. A linear programming model is used to simulate the power system, and two sets of states, mission states and damage states, are formulated to simulate the stochastic scenarios with which the IEP may be confronted. A genetic algorithm is applied to the design of IEP to find optimized energy storage control parameters. By using this algorithm, the maximum average performance of power system is found.

Nowadays islanding has become a big issue with the increasing use of distributed generators in power system. In order to effectively detect islanding after DG disconnects from main source, author first studied two passive islanding methods in this thesis: THD&VU method and wavelet-transform method. Compared with other passive methods, each of them has small non-detection zone, but both of them are based on the threshold limit, which is very hard to set. What’s more, when these two methods were applied to practical signals distorted with noise, they performed worse than anticipated. Thus, a new composite intelligent based method is presented in this thesis to solve the drawbacks above. The proposed method first uses wavelet-transform to detect the occurrence of events (including islanding and non-islanding) due to its sensitivity of sudden change. Then this approach utilizes artificial neural network (ANN) to classify islanding and non-islanding events. In this process, three features based on THD&VU are extracted as the input of ANN classifier. The performance of proposed method was tested on two typical distribution networks. The obtained results of two cases indicated the developed method can effectively detect islanding with low misclassification.

Recently, more and more disputations about how demand response should be compensated have arisen. Moreover, the court is about to rehear the Order 745. It probably will have significant impact on the whole working system used to be built for demand response before. Nowadays, some power companies and utilities think that they will endure profits leakage while demand response resources still are compensated. In this research, knowledge of demand response, local marginal price, Order 745 and other related concept will be explained in detail in case of misunderstanding. Associated with all these knowledge, a possible compensation method will be proposed. It combines many existing compensation methods. It mainly can be divided into three parts, i.e., high load period, off-peak period and low load period. The demand response resources will be compensated appropriately through these three periods. The compensation method endeavors to be just and reasonable.

The digitization of classical control systems presents a number of challenges and opportunities with respect to the miniaturization, distribution, reliability verification and obsolescence of both the controller and the underlying system under control. A method for the design of proportional-integral-derivative (PID) compensators realized in the form of all-digital components is presented. All-digital refers to a system implementation that is realizable with a wide range of digital logic components including discrete digital logic elements and programmable logic devices (PLDs) such as field-programmable gate arrays. The proportional, integral and derivative components of the classical PID control law were re-envisioned in terms of frequency of occurrences or counts for adaptation to combinatorial and sequential digital logic. Modification of the control scheme around this newly formed representation of system error enables the development of a PID-like FPGA-based or PLD-based controller. Details of the design of an all-digital PID-like controller including abstract, causal block diagrams and a MATLAB® and Simulink® based implementation are presented. The compensator was simulated in a velocity tracking DC motor control application and was found to perform comparably to that of a classical PID based control. Methods for assessing the resultant stability of an all-digital PID compensated system under control are discussed.

Gas Metal Arc Welding (GMAW) is one of the most important welding processes in industrial application. To control metal transfer at given variables is a focus in the field of research and development in welding community. In this dissertation, laser enhanced GMAW is proposed and developed by adding a lower power laser onto the droplet to generate an auxiliary detaching force. The electromagnetic force needed to detach droplets, thus the current that determines this force, is reduced. Wire feed speed, arc voltage, and laser intensity were identified as three major parameters that affect the laser enhanced metal transfer process and a systematic series of experiments were designed and conducted to test these parameters. The behaviors of the laser enhanced metal transfer process observed from high speed images were analyzed using the established physics of metal transfer. In all experiments, the laser was found to affect the metal transfer process as an additional detaching force that tended to change a short-circuiting transfer to drop globular or drop spray, reduce the diameter of the droplet detached in drop globular transfer, or decrease the diameter of the droplet such that the transfer changed from drop globular to drop spray. The enhancement of the laser was found to increase as the laser intensity increased. The larger laser intensity tended to help reduce the size of the droplet detached. The arc voltage affected the metal transfer process through changing the current and changing the gap and possible time interval of the droplet development. A larger arc voltage helped reduce the size of the droplet detached through an increased electromagnetic force. Desired heat input and current/arc pressure waveforms may thus be both delivered and controlled by GMAW through laser enhancement. Laser recoil pressure force was estimated based on the difference of gravitational force with and without laser pulse, and the result was with an acceptable accuracy. Good formation of welds and full penetration of thin plate could be obtained using laser enhanced GMAW. A nonlinear model was established to simulate the dynamic metal transfer in laser enhanced GMAW, and the results agree with the experimental one.

Wide-area camera networks are becoming more and more common. They have widerange of commercial and military applications from video surveillance to smart home and from traffic monitoring to anti-terrorism. The design of such a camera network is a challenging problem due to the complexity of the environment, self and mutual occlusion of moving objects, diverse sensor properties and a myriad of performance metrics for different applications. In this dissertation, we consider two such challenges: camera planing and camera fusion. Camera planning is to determine the optimal number and placement of cameras for a target cost function. Camera fusion describes the task of combining images collected by heterogenous cameras in the network to extract information pertinent to a target application. I tackle the camera planning problem by developing a new unified framework based on binary integer programming (BIP) to relate the network design parameters and the performance goals of a variety of camera network tasks. Most of the BIP formulations are NP hard problems and various approximate algorithms have been proposed in the literature. In this dissertation, I develop a comprehensive framework in comparing the entire spectrum of approximation algorithms from Greedy, Markov Chain Monte Carlo (MCMC) to various relaxation techniques. The key contribution is to provide not only a generic formulation of the camera planning problem but also novel approaches to adapt the formulation to powerful approximation schemes including Simulated Annealing (SA) and Semi-Definite Program (SDP). The accuracy, efficiency and scalability of each technique are analyzed and compared in depth. Extensive experimental results are provided to illustrate the strength and weakness of each method. The second problem of heterogeneous camera fusion is a very complex problem. Information can be fused at different levels from pixel or voxel to semantic objects, with large variation in accuracy, communication and computation costs. My focus is on the geometric transformation of shapes between objects observed at different camera planes. This so-called the geometric fusion approach usually provides the most reliable fusion approach at the expense of high computation and communication costs. To tackle the complexity, a hierarchy of camera models with different levels of complexity was proposed to balance the effectiveness and efficiency of the camera network operation. Then different calibration and registration methods are proposed for each camera model. At last, I provide two specific examples to demonstrate the effectiveness of the model: 1)a fusion system to improve the segmentation of human body in a camera network consisted of thermal and regular visible light cameras and 2) a view dependent rendering system by combining the information from depth and regular cameras to collecting the scene information and generating new views in real time.

Over the last two decades, functions of the embedded systems have evolved from simple real-time control and monitoring to more complicated services. Embedded systems equipped with powerful chips can provide the performance that computationally demanding information processing applications need. However, due to the power issue, the easy way to gain increasing performance by scaling up chip frequencies is no longer feasible. Recently, low-power architecture designs have been the main trend in embedded system designs. In this dissertation, we present our approaches to attack the energy-related issues in embedded system designs, such as thermal issues in the 3D chip multiprocessor (CMP), the endurance issue in the phase-change memory(PCM), the battery issue in the embedded system designs, the impact of inaccurate information in embedded system, and the cloud computing to move the workload to remote cloud computing facilities. We propose a real-time constrained task scheduling method to reduce peak temperature on a 3D CMP, including an online 3D CMP temperature prediction model and a set of algorithm for scheduling tasks to different cores in order to minimize the peak temperature on chip. To address the challenging issues in applying PCM in embedded systems, we propose a PCM main memory optimization mechanism through the utilization of the scratch pad memory (SPM). Furthermore, we propose an MLC/SLC configuration optimization algorithm to enhance the efficiency of the hybrid DRAM + PCM memory. We also propose an energy-aware task scheduling algorithm for parallel computing in mobile systems powered by batteries. When scheduling tasks in embedded systems, we make the scheduling decisions based on information, such as estimated execution time of tasks. Therefore, we design an evaluation method for impacts of inaccurate information on the resource allocation in embedded systems. Finally, in order to move workload from embedded systems to remote cloud computing facility, we present a resource optimization mechanism in heterogeneous federated multi-cloud systems. And we also propose two online dynamic algorithms for resource allocation and task scheduling. We consider the resource contention in the task scheduling.

Scanning-electron-beam lithography (SEBL) is the primary technology to generate arbitrary features at the nano-scale. However, pattern placement accuracy still remains poor compared to its resolution due to the open-loop nature of SEBL systems. Vibration, stray electromagnetic fields, deflection distortion and hysteresis, substrate charging, and other factors prevent the electron-beam from reaching its target position and one has no way to determine the actual beam position during patterning with conventional systems. To improve the pattern placement accuracy, spatial-phase-locked electron-beam lithography (SPLEBL) provides feedback control of electron-beam position by monitoring the secondary electron signal from electron-transparent fiducial grids on the substrate. While scanning the electron beam over the fiducial grids, the phase of the grid signal is analyzed to estimate the electron-beam position error; then the estimates are sent back to beam deflection system to correct the position error. In this way, closed-loop control is provided to ensure pattern placement accuracy. The implementation of spatial-phase-locking on high speed field-programmable gate array (FPGA) provides a low-cost method to create a nano-manufacturing platform with 1 nm precision and significantly improved throughput. Shot-to-shot, or pixel-to-pixel, dose variation during EBL is a significant practical and fundamental problem. Dose variations associated with charging, electron source instability, optical system drift, and ultimately shot noise in the beam itself conspire to increase critical dimension variability and line width roughness and to limit the throughput. It would be an important improvement to e-beam patterning technology if real-time feedback control of electron-dose were provided to improve pattern quality and throughput even beyond the shot noise limit. A novel approach is proposed in this document to achieve the real-time dose control based on the measurement of electron arrival at the sample to be patterned, rather than from the source or another point in the electron-optical system. A dose control algorithm, implementation on FPGA, and initial experiment results for the real-time feedback dose control on the e-beam patterning tool is also presented.

This dissertation develops surface integral equations using constraint-based Helmholtz decompositions for electromagnetic modeling. This new approach is applied to the electric field integral equation (EFIE), and it incorporates a Helmholtz decomposition (HD) of the current. For this reason, the new formulation is referred to as the EFIE-hd. The HD of the current is accomplished herein via appropriate surface integral constraints, and leads to a stable linear system. This strategy provides accurate solutions for the electric and magnetic fields at both high and low frequencies, it allows for the use of a locally corrected Nyström (LCN) discretization method for the resulting formulation, it is compatible with the local global solution framework, and it can be used with non-conformal meshes. To address large-scale and complex electromagnetic problems, an overlapped localizing local-global (OL-LOGOS) factorization is used to factorize the system matrix obtained from an LCN discretization of the augmented EFIE (AEFIE). The OL-LOGOS algorithm provides good asymptotic performance and error control when used with the AEFIE. This application is used to demonstrate the importance of using a well-conditioned formulation to obtain efficient performance from the factorization algorithm.

Surface-plasmon-resonance (SPR) sensors are widely used in biological, chemical, medical, and environmental sensing. This dissertation describes the design and development of dual-mode, self-referencing SPR sensors supporting two surface-plasmon modes (long- and short-range) which can differentiate surface binding interactions from bulk index changes at a single sensing location. Dual-mode SPR sensors have been optimized for surface limit of detection (LOD). In a wavelength interrogated optical setup, both surface plasmons are simultaneously excited at the same location and incident angle but at different wavelengths. To improve the sensor performance, a new approach to dual-mode SPR sensing is presented that offers improved differentiation between surface and bulk effects. By using an angular interrogation, both surface plasmons are simultaneously excited at the same location and wavelength but at different angles. Angular interrogation offers at least a factor of 3.6 improvement in surface and bulk cross-sensitivity compared to wavelength-interrogated dual-mode SPR sensors. Multi-mode SPR sensors supporting at least three surface-plasmon modes can differentiate a target surface effect from interfering surface effects and bulk index changes. This dissertation describes a tri-mode SPR sensor which supports three surface plasmon resonance modes at one single sensing position, where each mode is excited at a different wavelength. The tri-mode SPR sensor can successfully differentiate specific binding from the non-specific binding and bulk index changes.