Doctor of Philosophy / Department of Electrical and Computer Engineering / Balasubramaniam Natarajan / A cyber physical system (CPS) is an intelligent integration of computation and communication infrastructure for monitoring and/or control of an underlying physical system. In this dissertation, we consider a specific class of CPS architectures where state of the system is spatially distributed in physical space. Examples that fit this category of CPS include, smart distribution gird, smart highway/transportation network etc. We study state estimation and control process in such systems where, (1) multiple sensors and actuators are arbitrarily deployed to jointly sense and control the system; (2) sensors directly communicate their observations to a central estimation and control unit (ECU) over communication links; and, (3) the ECU, on computing the control action, communicates control actions to actuators over communication links. Since communication links are susceptible to random failures, the overall estimation and control process is subjected to: (1) partial observation updates in estimation process; and (2) partial actuator actions in control process. We analyze stochastic stability of estimation and control process, in this scenario by establishing the conditions under which estimation accuracy and deviation from desired state trajectory is bounded. Our key contribution is the derivation of a new fundamental result on bounds for critical probabilities of individual communication link failure to maintain stability of overall system. The overall analysis illustrates that there is trade-off between stability of estimation and control process and quality of underlying communication network. In order to demonstrate practical implication of our work, we also present a case study in smart distribution grid as a system example of spatially distributed CPSs. Voltage/VAR support via distributed generators is studied in a stochastic nonlinear control framework.

Master of Science / Department of Electrical & Computer Engineering / Steve Warren / Activity recognition can be an important part of human health awareness. Many benefits can be generated from the recognition results, including knowledge of activity intensity as it relates to wellness over time. Various activity-recognition techniques have been presented in the literature, though most address simple activity-data collection and off-line analysis. More sophisticated real-time identification is less often addressed. Therefore, it is promising to consider the combination of current off-line, activity-detection methods with wearable, embedded tools in order to create a real-time wireless human activity recognition system with improved accuracy. Different from previous work on activity recognition, the goal of this effort is to focus on specific activities that an astronaut may encounter during a mission. Planetary navigation field test (PNFT) tasks are designed to meet this need. The approach used by the KSU team is to pre-record data on the ground in normal earth gravity and seek signal features that can be used to identify, and even predict, fatigue associated with these activities. The eventual goal is to then assess/predict the condition of an astronaut in a reduced-gravity environment using these predetermined rules. Several classic machine learning algorithms, including the k-Nearest Neighbor, Naïve Bayes, C4.5 Decision Tree, and Support Vector Machine approaches, were applied to these data to identify recognition algorithms suitable for real-time application. Graphical user interfaces (GUIs) were designed for both MATLAB and LabVIEW environments to facilitate recording and data analysis. Training data for the machine learning algorithms were recorded while subjects performed each activity, and then these identification approaches were applied to new data sets with an identification accuracy of around 86%. Early results indicate that a single three-axis accelerometer is sufficient to identify the occurrence of a given PNFT activity. A custom, embedded acceleration monitoring system employing ZigBee transmission is under development for future real-time activity recognition studies. A different GUI has been implemented for this system, which uses an on-line algorithm that will seek to identify activity at a refresh rate of 1 Hz.

Master of Science / Department of Electrical and Computer Engineering / William B. Kuhn / This work was a part of NASA EPSCoR Project NNX11AM05A: Biosensor Networks and Telecommunication Subsystems for Long Duration Missions, EVA Suits, and Robotic Precursor Scout Missions. The project’s main goal is the development of a wireless sensor network inside an astronaut’s spacesuit. Antennas are essential components in a wireless network. Since this antenna will be used inside the spacesuit it is important to consider both the physical size limitations and the desired antenna polarization. After exploring the WWVB radio station antenna which provides the preferred vertical polarization and has a suitable aspect ratio, the top hat antenna seemed promising for intrasuit communication. The design of a top hat antenna is outlined. Then, the antennas were tested using 433 MHz radios in a full scale model spacesuit. This spacesuit was designed specifically to model the behavior of aluminized mylar in the real suit. Test results support the feasibility of an intrasuit wireless network. If a gateway radio is placed on the chest or back, a sensor could be placed anywhere on the body and provide an adequate signal. These initial tests did not include a matching network, but the additional link-margin afforded by a matching network, even an imperfect match, is considered. Energy harvesting is explored as an alternative to batteries powering the intrasuit radio. In the oxygen rich environment of a spacesuit, even the smallest spark can be catastrophic. A variety of energy harvesting options are explored with a focus on thermal energy harvesting. The temperature difference between the human skin and the astronaut’s Liquid Cooling and Ventilation Garment can be used to produce a small voltage. To increase the voltage a step-up converter is implemented. Final integration of the two systems with a biosensor is left for on-going work in the three year NASA project.

Doctor of Philosophy / Department of Electrical and Computer Engineering / Caterina Scoglio / The science of complex networks has significantly advanced in the last decade and has provided valuable insights into the properties of real world systems by evaluating their structure and construction. Several phenomena occurring in real technological and social systems can be studied, evaluated, quantified, and remedied with the help of network science. The electric power grid is one such real technological system that can be studied through the science of complex networks. The electric grid consists of three basic sub-systems: Generation, Transmission, and Distribution. The transmission sub-system is of particular interest in this work because its mesh-like structure offers challenging problems to complex networks researchers. Cascading dynamics of power grids is one of the problems that can be studied through complex networks. The North American Electric Reliability Corporation (NERC) defines a cascading failure as the uncontrolled successive loss of system elements triggered by an incident at any location. In this dissertation, we primarily discuss the dynamics of cascading failures in the power transmission grid, from a complex networks perspective, and propose possible solutions for mitigating their effects. We evaluate the grid dynamics for two specific scenarios, load growth and random fluctuations in the grid, to study the behavior of the grid under critical conditions. Further, we propose three mitigation strategies for reducing the damage caused by cascading failures. The first strategy is intentional islanding in the power transmission grid. The aim of this method is to intentionally split the grid into two or more separate self- sustaining components such that the initial failure is isolated and the separated components can function independently, with minimum load shedding. The second mitigation strategy involves controlled placement of distributed generation (DG) in the transmission system in order to enhance robustness of the grid. The third strategy requires the addition of a link in the transmission grid by reduction of the average spectral distance, utilizing the Ybus matrix of the grid and a novel algorithm. Through this dissertation, we aim to successfully cover the gap present in the complex networks domain, with respect to the vulnerability analysis of power grid networks.

Doctor of Philosophy / Department of Electrical and Computer Engineering / Caterina Maria Scoglio / We have analytically discovered the existence of two global epidemic invasion thresholds in a directed meta-population network model of the United States cattle industry. The first threshold describes the outbreak of disease first within the core of the livestock system while the second threshold describes the invasion of the epidemic into a second class of locations where the disease would pose a risk for contamination of meat production. Both thresholds have been verified through extensive numerical simulations. We have further derived the relationship between the pair of thresholds and discovered a unique dependence on the network topology through the fractional compositions and the in-degree distributions of the transit and sink nodes. We then addressed a major challenge for epidemiologists and their efforts to model disease outbreaks in cattle. There is a critical shortfall in the availability of large-scale livestock movement data for the United States. We meet this challenge by developing a method to estimate cattle movement parameters from publicly available data. Across 10 Central States of the US, we formulated a large, convex optimization problem to predict the cattle movement parameters which, having minimal assumptions, provide the best fit to the US Department of Agriculture's Census database and follow constraints defined by scientists and cattle experts. Our estimated parameters can produce distributions of cattle shipments by head which compare well with shipment distributions also provided by the US Department of Agriculture. This dissertation concludes with a brief incorporation of the analytic models and the parameter estimation. We approximated the critical movement rates defined by the global invasion thresholds and compared them with the average estimated cattle movement rates to find a significant opportunity for epidemics to spread through US cattle populations.

Doctor of Philosophy / Department of Electrical and Computer Engineering / Sanjoy Das and Anil Pahwa / Because a majority of day-to-day activities rely on electricity, it plays an important role in daily life. In this digital world, most of the people’s life depends on electricity. Without electricity, the flip of a switch would no longer produce instant light, television or refrigerators would be nonexistent, and hundreds of conveniences often taken for granted would be impossible. Electricity has become a basic necessity, and so any interruption in service due to disturbances in power lines causes a great inconvenience to customers. Customers and utility commissions expect a high level of reliability. Power distribution systems are geographically dispersed and exposure to environment makes them highly vulnerable part of power systems with respect to failures and interruption of service to customers. Following the restructuring and increased competition in the electric utility industry, distribution system reliability has acquired larger significance. Better understanding of causes and consequences of distribution interruptions is helpful in maintaining distribution systems, designing reliable systems, installing protection devices, and environmental issues. Various events, such as equipment failure, animal activity, tree fall, wind, and lightning, can negatively affect power distribution systems. Weather is one of the primary causes affecting distribution system reliability. Unfortunately, as weather-related outages are highly random, predicting their occurrence is an arduous task. To study the impact of weather on overhead distribution system several models, such as linear and exponential regression models, neural network model, and ensemble methods are presented in this dissertation. The models were extended to study the impact of animal activity on outages in overhead distribution system. Outage, lightning, and weather data for four different cities in Kansas of various sizes from 2005 to 2011 were provided by Westar Energy, Topeka, and state climate office at Kansas State University weather services. Models developed are applied to estimate daily outages. Performance tests shows that regression and neural network models are able to estimate outages well but failed to estimate well in lower and upper range of observed values. The introduction of committee machines inspired by the ‘divide & conquer” principle overcomes this problem. Simulation results shows that mixture of experts model is more effective followed by AdaBoost model in estimating daily outages. Similar results on performance of these models were found for animal-caused outages.

Master of Science / Department of Electrical and Computer Engineering / William B. Kuhn / RF frequency synthesizer systems are prevalent in today’s electronics. In a synthesizer there is a sensitive analog oscillator that may be affected by two different types of noise. The first is random noise injection from active devices. This results in phase noise in the synthesizer’s spectrum. The second noise source is deterministic. A digital frequency divider with high-amplitude switching is an example of such a deterministic source. This noise enters the system through various forms of electric or magnetic field coupling and manifests itself as spurs or pulling. Both forms of noise can adversely affect system performance. We will first summarize methods for reducing noise. These already known steps have to do with layout techniques, device geometry, and general synthesizer topologies. Then we will show ways to isolate noisy interfering circuits from the sensitive analog systems. Finally, we present some considerations for reducing the effects of random noise. A power supply filter can improve the effects of deterministic noise such as undesired signals on the supply line. We show several ways to improve the rejection of high frequency supply noise (characterized by the power supply rejection ratio or PSRR) through the design of a voltage regulator. The emphasis is on new techniques for obtaining good PSRR at S-band frequencies and above. To validate the techniques, we designed a regulator in Peregrine Semiconductor’s .25µm ULTRA CMOS Silicon on Sapphire process. It produces a 2.5V output with an input ranging from 2.6V to 5V and has a maximum current sourcing of 70mA. The regulator’s low drop out performance is 60mV with no load and it achieves a power supply ripple reduction of 29.8 dB at 500 MHz. To address random noise in synthesizers, the thesis provides preliminary investigation of an oscillator topology change that has been proposed in the literature. This proposed change reduces the phase noise of the oscillator within the overall system. A differential cross-coupled design is the usual topology of choice, but it is not optimal for noise performance. We investigate current noise injection in the traditional design and present an updated design that uses a differential Colpitts oscillator as an alternative to classic cross-coupled designs.

Master of Science / Department of Electrical Engineering / William Kuhn / When enough charges accumulate on two objects, the air dielectric between them breaks down to create a phenomenon known as electrostatic discharge (ESD). ESD is of great concern in the integrated circuit industry because of the damage it can cause to ICs. The problem will only become worse as process components become smaller. The three main types of ESD experienced by an IC are the human body model (HBM), the charged device model (CDM), and the machine model (MM). HBM ESD has the highest voltage while CDM ESD has the highest bandwidth and current of the three ESD types. Integrated circuits generally include ESD protection circuitry connected to their pads. Pads are the connection between the IC and the outside world, making them the required location for circuitry designed to route ESD events away from the IC's internal circuitry. The most basic protection pads use diodes connected from I/O to VDD and I/O to ground. A voltage clamp between VDD and ground is also necessary to protect against CDM and MM event types where the device may not yet have a low impedance supply path connected. The purpose of this research is to investigate the performance of ESD circuits and to develop a method for detecting the occurrence of an ESD event in an integrated circuit by utilizing IC fuses. The combination of IC fuses and detection circuitry designed to sense a broken fuse allows the IC to perform a built-in self-test (BIST) for ESD to identify compromised ICs, preventing manufacturers from shipping damaged circuits. Simulations are used to design an optimized protection circuit to complement the proposed ESD detection circuit. Optimization of an ESD pad circuit increases the turn-on speed of its voltage clamps and decreases the series resistance of its protection diodes. These improvements minimize the stress voltage placed on internal circuitry due to an ESD event. An ESD measurement setup is established and used to verify voltage clamp operation. This research also proposes an ESD detection circuit based on IC fuses, which fail during an ESD event. A variety of IC fuses are tested using the ESD measurement setup as well as a TLP setup in order to determine the time and current needed for them to break. Suitable IC fuses have a resistance less than 5 Ω and consistently break during the first trial.

Master of Science / Department of Electrical and Computer Engineering / Sanjoy Das / Anil Pahwa / Outage management describes system utilized by electric distribution utilities to help restore power in event of an outage. The complexity of outage management system employed by different utilities to determine the location of fault could differ. First step of outage management is to know where the problem is. Utilities typically depend on customers to call and inform them of the problem by entering their addresses. After sufficient calls are received, the utility is able to pinpoint the location of the outage. This part of outage management is called trouble call analysis. In event of fault in a feeder of a radial distribution system, the upstream device or the device that serves to protect that particular zone activates and opens the circuit. This particular device is considered as the operated protective device. The knowledge of the activated protective device can help locate the fault. Repair crews could be sent to that particular location to carry out power restoration efforts. The main objective of this work is to study model of distribution system that could utilize the network topology and customer calls to predict the location of the operated protective device. Such prediction would be based on the knowledge of the least amount of variables i.e. network topology and customer calls. Radial distribution systems are modeled using the immune system algorithm and test cases with trouble calls are simulated in MATLAB to test the effectiveness of the proposed technique. Also, the proposed technique is tested on an actual feeder circuit with real call scenarios to verify against the known fault locations.

Master of Science / Department of Electrical and Computer Engineering / Dwight Day / High-performance computing is often limited by memory access. As speeds increase, processors are often waiting on data transfers to and from memory. Classic memory controllers focus on delivering sequential memory as quickly as possible. This will increase the performance of instruction reads and sequential data reads and writes. However, many applications in high-performance computing often include random memory access which can limit the performance of the system. Techniques such as scatter/gather can improve performance by allowing nonsequential data to be written and read in a single operation. Caching can also improve performance by storing some of the data in memory local to the processor. In this project, we try to find the benefits of different cache configurations. The different configurations include different cache line sizes as well as total size of cache. Although a range of benchmarks are typically used to test performance, we focused on a conjugate gradient solver, HPCCG. The program HPCCG incorporates many of the elements of common benchmarks used in high-performance computing, and relates better to a real world problem. Results show that the performance of a cache configuration can depend on the size of the problem. Problems of smaller sizes can benefit more from a larger cache, while a smaller cache may be sufficient for larger problems.