Engineering Commons^™

Contributions To The Theory And Application Of Multiple Model Estimation, Alia R. Strandt

Dissertations (1934 -)

Multiple model estimation is a versatile technique that has been applied in a large variety of adaptive estimation problems. In this technique, several estimators, each designed around a possible model of the system, are used in parallel, and the estimator that most closely models the true system is determined using Bayes’ Rule. In this dissertation, convergence properties of the multiple model estimation algorithm are investigated, including a proof of convergence and factors that influence convergence time. In addition, the multiple model estimation algorithm is applied in two parameter estimation problems.The first half of the dissertation focuses on properties of the …

Probabilistic Framework For Balancing Smart Grid's Performance Enhancement And Resilience To Cyber Threat, Rezoan Ahmed Shuvro

Dissertations (1934 -)

Critical infrastructures such as smart grids rely heavily on the seamless interaction between the grid subcomponents, i.e., the communication networks which transfers information from and to the grid, and the human operators/AI agents for taking necessary control actions. Smart grids are prone to cascading failures, which trigger from a few initial the tripping of a few transmission lines or generators, creating a ripple effect in the entire network, which may, in turn, lead to a total blackout. Having additional information through the communication network increases the probability of taking better control actions (e.g., effective load shedding and other protection mechanisms), …

An Unsupervised Cluster: Learning Water Customer Behavior Using Variation Of Information On A Reconstructed Phase Space, Michele Rae Bizub Malinowski

Dissertations (1934 -)

The unsupervised clustering algorithm described in this dissertation addresses the need to divide a population of water utility customers into groups based on their similarities and differences, using only the measured flow data collected by water meters. After clustering, the groups represent customers with similar consumption behavior patterns and provide insight into ‘normal’ and ‘unusual’ customer behavior patterns. This research focuses upon individually metered water utility customers and includes both residential and commercial customer accounts serviced by utilities within North America. The contributions of this dissertation not only represent a novel academic work, but also solve a practical problem for …

Analysis Of Sensor Signals For Online Detection Of Hydrocarbons In Liquids In The Presence Of Interferents, Karthick Sothivelr

Dissertations (1934 -)

Current applicability of many chemical sensors is limited due to the lack of adequate selectivity to enable real-world applications. Often, the chemically sensitive element of the sensor is only partially selective to any specific target analyte, potentially giving rise to low probability of detection. Other challenges include the need to identify and quantify the target analytes in a mixture, especially in the presence of non-target interferents. In this dissertation, to enhance the selectivity of the sensor, analysis of sensor signals for detection and quantification of mixtures of hydrocarbon compounds in liquids in the presence of interferents using estimation theory and …

Quantifying Forecast Uncertainty In The Energy Domain, Mohammad Saber

Dissertations (1934 -)

This dissertation focuses on quantifying forecast uncertainties in the energy domain, especially for the electricity and natural gas industry. Accurate forecasts help the energy industry minimize their production costs. However, inaccurate weather forecasts, unusual human behavior, sudden changes in economic conditions, unpredictable availability of renewable sources (wind and solar), etc., represent uncertainties in the energy demand-supply chain. In the current smart grid era, total electricity demand from non-renewable sources influences by the uncertainty of the renewable sources. Thus, quantifying forecast uncertainty has become important to improve the quality of forecasts and decision making. In the natural gas industry, the task …

Performance-Robust Dynamic Feedback Control Of Lipschitz Nonlinear Systems, Winston Baker

Dissertations (1934 -)

This dissertation addresses the dynamic control of nonlinear systems with finite energy noise in the state and measurement equations. Regional eigenvalue assignment (REA) is used to ensure that the state estimate error is driven to zero significantly faster than the state itself. Moreover, the controller is designed for the resulting closed loop system to achieve any one of a set of general performance criteria (GPC). The nonlinear model is assumed to have a Lipschitz nonlinearity both in the state and measurement equations. By using the norm bound of the nonlinearity, the controller is designed to be robust against all nonlinearities …

Robust And Resilient Control Design And Performance Analysis For Uncertain Systems With Finite Energy Disturbances, Fan Feng

Dissertations (1934 -)

This dissertation addresses the problem of robust and resilient control design with additional performance analysis for uncertain systems with finite energy disturbances. The control design is robust and resilient in the sense of maintaining certain performance criteria in the presence of perturbations in both system parameters and feedback gains. The performance analysis evaluates resilience properties of state feedback and dynamic (state estimate) feedback controllers. A resilient and robust state feedback controller is designed using linear matrix inequality (LMI) techniques for the characterization of solutions to the analysis and design problems posed in this work. Uncertainties are allowed in the linear …

Design Optimization Of Permanent Magnet Machines Over A Target Operating Cycle Using Computationally Efficient Techniques, Alireza Fatemi

Dissertations (1934 -)

The common practices of large-scale finite element (FE) model-based design optimization of permanent magnet synchronous machines (PMSMs) oftentimes aim at improving the machine performance at the rated operating conditions, thus overlooking the performance treatment over the entire range of operation in the constant torque and extended speed regions. This is mainly due to the computational complexities associated with several aspects of such large-scale design optimization problems, including the FE-based modeling techniques, large number of load operating points for load-cycle evaluation of the design candidates, and large number of function evaluations required for identification of the globally optimal design solutions. In …

Development Of A Wireless Mobile Computing Platform For Fall Risk Prediction, Akm Jahangir Alam Majumder

Dissertations (1934 -)

Falls are a major health risk with which the elderly and disabled must contend. Scientific research on smartphone-based gait detection systems using the Internet of Things (IoT) has recently become an important component in monitoring injuries due to these falls. Analysis of human gait for detecting falls is the subject of many research projects. Progress in these systems, the capabilities of smartphones, and the IoT are enabling the advancement of sophisticated mobile computing applications that detect falls after they have occurred. This detection has been the focus of most fall-related research; however, ensuring preventive measures that predict a fall is …

Novel Convergence Results In Nonlinear Filtering, Jennifer Lynn Bonniwell

Dissertations (1934 -)

In this dissertation, the discrete-time extended Kalman filter is analyzed for its ability to attenuate finite-energy disturbances, known as the H-infinity property. Though the extended Kalman filter is designed to be a locally optimal minimum variance estimator, this dissertation proves that it has additional properties, such as H-infinity. This analysis is performed with the extended Kalman filter in direct form. Since this form reduces assumptions placed on the system in previous works on convergence and H-2 properties of the extended Kalman filter, the extended Kalman filter used as a nonlinear observer for noise-free models is revisited using the direct form …

Data Cleaning In The Energy Domain, Hermine Nathalie Akouemo Kengmo Kenfack

Dissertations (1934 -)

This dissertation addresses the problem of data cleaning in the energy domain, especially for natural gas and electric time series. The detection and imputation of anomalies improves the performance of forecasting models necessary to lower purchasing and storage costs for utilities and plan for peak energy loads or distribution shortages. There are various types of anomalies, each induced by diverse causes and sources depending on the field of study. The definition of false positives also depends on the context. The analysis is focused on energy data because of the availability of data and information to make a theoretical and practical …

Speaker Independent Acoustic-To-Articulatory Inversion, An Ji

Dissertations (1934 -)

Acoustic-to-articulatory inversion, the determination of articulatory parameters from acoustic signals, is a difficult but important problem for many speech processing applications, such as automatic speech recognition (ASR) and computer aided pronunciation training (CAPT). In recent years, several approaches have been successfully implemented for speaker dependent models with parallel acoustic and kinematic training data. However, in many practical applications inversion is needed for new speakers for whom no articulatory data is available. In order to address this problem, this dissertation introduces a novel speaker adaptation approach called Parallel Reference Speaker Weighting (PRSW), based on parallel acoustic and articulatory Hidden Markov Models …

Surface Acoustic Wave (Saw)-Based Gas Flow Sensor, Nisar Ahmad

Dissertations (1934 -)

There has been a growing interest in using SAW devices for sensing various physical parameters such as pressure, acceleration, temperature, and gas. The current research has been undertaken to derive a model of a SAW-based gas flow rate sensor, using the principle of heat transfer with the flow of gas. It consists of a SAW delay line fabricated on a suitable substrate and a thin film heater to heat the SAW device to a suitable temperature above the ambient. The delay line is connected in the feedback loop of an rf-amplifier resulting in a delay line stabilized SAW oscillator. When …

Theoretical Analysis Of Torsionally Vibrating Microcantilevers For Chemical Sensor Applications In Viscous Liquids, Tao Cai

Dissertations (1934 -)

Dynamically driven microcantilevers excited in the transverse (or out-of-plane) direction are widely used as highly sensitive chemical sensing platforms in various applications. While these devices work very well in air, their performance in liquids is not efficient because of the combination of increased viscous damping and effective fluid mass. In order to improve the characteristics of microcantilevers in liquid environments, some other vibration modes such as the torsional mode and lateral (or in-plane) flexural mode have been proposed.
In this work, the characteristics of torsionally vibrating rectangular microcantilevers with length L, width b and thickness h in viscous liquids are …

A Novel Design Optimization Of A Fault-Tolerant Ac Permanent Magnet Machine-Drive System, Peng Zhang

Dissertations (1934 -)

In this dissertation, fault-tolerant capabilities of permanent magnet (PM) machines were investigated. The 12-slot 10-pole PM machines with V-type and spoke-type PM layouts were selected as candidate topologies for fault-tolerant PM machine design optimization problems. The combination of 12-slot and 10-pole configuration for PM machines requires a fractional-slot concentrated winding (FSCW) layout, which can lead to especially significant PM losses in such machines. Thus, a hybrid method to compute the PM losses was investigated, which combines computationally efficient finite-element analysis (CE-FEA) with a new analytical formulation for PM eddy-current loss computation in sine-wave current regulated synchronous PM machines. These algorithms …

Physiologically-Motivated Feature Extraction Methods For Speaker Recognition, Jianglin Wang

Dissertations (1934 -)

Speaker recognition has received a great deal of attention from the speech community, and significant gains in robustness and accuracy have been obtained over the past decade. However, the features used for identification are still primarily representations of overall spectral characteristics, and thus the models are primarily phonetic in nature, differentiating speakers based on overall pronunciation patterns. This creates difficulties in terms of the amount of enrollment data and complexity of the models required to cover the phonetic space, especially in tasks such as identification where enrollment and testing data may not have similar phonetic coverage. This dissertation introduces new …

Theoretical Analysis Of Laterally Vibrating Hammerhead Microcantilever Sensors In A Viscous Liquid, Jinjin Zhang

Dissertations (1934 -)

Dynamically driven prismatic microcantilevers excited in the in-plane flexural mode have been investigated and used in liquid-phase sensing applications. However, the performance is restricted due to their limited surface sensing area and higher stiffness in shorter and wider prismatic microcantilevers. To increase the surface sensing area, and further improve sensing characteristics, it has been proposed to investigate symmetric hammerhead microcantilevers vibrating laterally in viscous liquid media. In this work, a theoretical model is proposed and the characteristics of the microcantilevers with symmetric shaped hammerheads (isosceles trapezoid, semi-circle, uniform rectangle and composite rectangle) are investigated. In the analysis, the stem of …

Predictive Pattern Discovery In Dynamic Data Systems, Wenjing Zhang

Dissertations (1934 -)

This dissertation presents novel methods for analyzing nonlinear time series in dynamic systems. The purpose of the newly developed methods is to address the event prediction problem through modeling of predictive patterns. Firstly, a novel categorization mechanism is introduced to characterize different underlying states in the system. A new hybrid method was developed utilizing both generative and discriminative models to address the event prediction problem through optimization in multivariate systems.

Secondly, in addition to modeling temporal dynamics, a Bayesian approach is employed to model the first-order Markov behavior in the multivariate data sequences. Experimental evaluations demonstrated superior performance over conventional …

Finite-Time Control And Estimation Of Nonlinear Systems With Disturbance Attenuation, Mohammad N. Elbsat

Dissertations (1934 -)

This dissertation addresses the mixed criteria finite-time bounded controller and observer design of certain classes of nonlinear systems. Finite-time bounded controllers and observers are used to guarantee performance bounds on the transient response of the systems considered. A robust and resilient mixed criteria state-feedback controller design is developed for a class of nonlinear systems with conic-type nonlinearities lying within a hypersphere of uncertain center, additive disturbances, and controller gain perturbations in discrete and continuous-time. Furthermore, a robust and resilient mixed criteria state-dependent state-feedback controller design is developed for a class of nonlinear systems with state dependent system matrices and state-dependent …

Disaggregating Time Series Data For Energy Consumption By Aggregate And Individual Customer, Steven Vitullo

Dissertations (1934 -)

This dissertation generalizes the problem of disaggregating time series data and describes the disaggregation problem as a mathematical inverse problem that breaks up aggregated (measured) time series data that is accumulated over an interval and estimates its component parts.

We describe five different algorithms for disaggregating time series data: the Naive, Time Series Reconstruction (TSR), Piecewise Linear Optimization (PLO), Time Series Reconstruction with Resampling (RS), and Interpolation (INT). The TSR uses least squares and domain knowledge of underlying correlated variables to generate underlying estimates and handles arbitrarily aggregated time steps and non-uniformly aggregated time steps. The PLO performs an adjustment …

Theoretical Analysis Of Laterally Vibrating Microcantilever Sensors In A Viscous Liquid Medium, Russell Cox

Dissertations (1934 -)

Dynamically driven microcantilevers are normally excited into resonance in the out-of-plane flexural mode. The beam's resonant frequency and quality factor are used to characterize the devices. The devices are well suited for operation in air, but are limited in viscous liquid media due to the increased viscous damping. In order to improve these characteristics, other vibration modes such as the in-plane (or lateral) flexural mode are investigated. In this work, microcantilevers vibrating in the in-plane flexural mode (or lateral direction) in a viscous liquid medium are investigated. The hydrodynamic forces on the microcantilever as a function of both Reynolds number …

Nonlinear Control And Estimation With General Performance Criteria, Xin Wang

Dissertations (1934 -)

This dissertation is concerned with nonlinear systems control and estimation with general performance criteria. The purpose of this work is to propose general design methods to provide systematic and effective design frameworks for nonlinear system control and estimation problems. First, novel State Dependent Linear Matrix Inequality control approach is proposed, which is optimally robust for model uncertainties and resilient against control feedback gain perturbations in achieving general performance criteria to secure quadratic optimality with inherent asymptotic stability property together with quadratic dissipative type of disturbance reduction. By solving a state dependent linear matrix inequality at each time step, the sufficient …

Analysis Of The Detection Of Organophosphate Pesticides In Aqueous Solutions Using Polymer-Coated Sh-Saw Devices, Arnold Kweku Mensah-Brown

Dissertations (1934 -)

Organophosphate pesticides (OPs) have been found as contaminants in surface and ground waters, soil, and agricultural products. Because OPs are toxic compounds, rapid detection/monitoring of OPs in groundwater is necessary to allow for real-time remediation. Detection of OPs in water has already been demonstrated using poly(epichlorohydrin) [PECH] and polyurethane as the sensing layers. However, the response times were relatively long, hindering real-time monitoring. In this work, a hybrid organic/inorganic chemically sensitive layer [bisphenol A-hexamethyltrisiloxane (BPA-HMTS)] that shows a high degree of partial selectivity for OPs is synthesized, characterized (in terms of the glass transition temperature, T_g, water stability, …