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Articles 151 - 180 of 251

Full-Text Articles in Applied Mathematics

Creating A Computational Tool To Simulate Vibration Control For Piezoelectric Devices, Ahmet Ozkan Ozer, Emma J. Moore Nov 2018

Creating A Computational Tool To Simulate Vibration Control For Piezoelectric Devices, Ahmet Ozkan Ozer, Emma J. Moore

Posters-at-the-Capitol

Piezoelectric materials have the unique ability to convert electrical energy to mechanical vibrations and vice versa. This project takes a stab to develop a reliable computational tool to simulate the vibration control of a novel “partial differential equation” model for a piezoelectric device, which is designed by integrating electric conducting piezoelectric layers constraining a viscoelastic layer to provide an active and lightweight intelligent structure. Controlling unwanted vibrations on piezoelectric devices (or harvesting energy from ambient vibrations) through piezoelectric layers has been the major focus in cutting-edge engineering applications such as ultrasonic welders and inchworms. The corresponding mathematical models for piezoelectric …


Robust Engineering Of Dynamic Structures In Complex Networks, Walter Botongo Bomela Aug 2018

Robust Engineering Of Dynamic Structures In Complex Networks, Walter Botongo Bomela

McKelvey School of Engineering Graduate Student Theses & Dissertations

Populations of nearly identical dynamical systems are ubiquitous in natural and engineered systems, in which each unit plays a crucial role in determining the functioning of the ensemble. Robust and optimal control of such large collections of dynamical units remains a grand challenge, especially, when these units interact and form a complex network. Motivated by compelling practical problems in power systems, neural engineering and quantum control, where individual units often have to work in tandem to achieve a desired dynamic behavior, e.g., maintaining synchronization of generators in a power grid or conveying information in a neuronal network; in this dissertation, …


Controllability And Observability Of The Discrete Fractional Linear State-Space Model, Duc M. Nguyen Apr 2018

Controllability And Observability Of The Discrete Fractional Linear State-Space Model, Duc M. Nguyen

Masters Theses & Specialist Projects

This thesis aims to investigate the controllability and observability of the discrete fractional linear time-invariant state-space model. First, we will establish key concepts and properties which are the tools necessary for our task. In the third chapter, we will discuss the discrete state-space model and set up the criteria for these two properties. Then, in the fourth chapter, we will attempt to apply these criteria to the discrete fractional model. The general flow of our objectives is as follows: we start with the first-order linear difference equation, move on to the discrete system, then the fractional difference equation, and finally …


Near-Optimal Control Of Switched Systems With Continuous-Time Dynamics Using Approximate Dynamic Programming, Tohid Sardarmehni Apr 2018

Near-Optimal Control Of Switched Systems With Continuous-Time Dynamics Using Approximate Dynamic Programming, Tohid Sardarmehni

Mechanical Engineering Research Theses and Dissertations

Optimal control is a control method which provides inputs that minimize a performance index subject to state or input constraints [58]. The existing solutions for finding the exact optimal control solution such as Pontryagin’s minimum principle and dynamic programming suffer from curse of dimensionality in high order dynamical systems. One remedy for this problem is finding near optimal solution instead of the exact optimal solution to avoid curse of dimensionality [31]. A method for finding the approximate optimal solution is through Approximate Dynamic Programming (ADP) methods which are discussed in the subsequent chapters.

In this dissertation, optimal switching in switched …


Analysis Of Temperature And Humidity Effects On Horizontal Photovoltaic Panels, Corey J. Booker Mar 2018

Analysis Of Temperature And Humidity Effects On Horizontal Photovoltaic Panels, Corey J. Booker

Theses and Dissertations

The United States Air Force seeks to address power grid vulnerability and bolster energy resilience through the use of renewable energy sources. Air Force Institute of Technology engineers designed and manufactured control systems to monitor power production from the most widely-used silicon-based solar cells at 38 testing locations around the globe spanning the majority of climate types. Researchers conducted multivariate regression analysis to establish a statistical relationship between photovoltaic power output, ambient temperature, and humidity pertaining to monocrystalline and polycrystalline photovoltaic panels. Formulated models first characterized power output globally, then by specific climate type with general inaccuracy. Location-specific models are …


Some Insights Into The Migration Of Double Imaginary Roots Under Small Deviation Of Two Parameters, Dina Alina Irofti, Keqin Gu, Islam Boussaada, Silviu-Iulian Niculescu Feb 2018

Some Insights Into The Migration Of Double Imaginary Roots Under Small Deviation Of Two Parameters, Dina Alina Irofti, Keqin Gu, Islam Boussaada, Silviu-Iulian Niculescu

SIUE Faculty Research, Scholarship, and Creative Activity

This paper studies the migration of double imaginary roots of the systems’ characteristic equation when two parameters are subjected to small deviations. The proposed approach covers a wide range of models. Under the least degeneracy assumptions, we found that the local stability crossing curve has a cusp at the point that corresponds to the double root, and it divides the neighborhood of this point into an S-sector and a G-sector. When the parameters move into the G-sector, one of the roots moves to the right halfplane, and the other moves to the left half-plane. When the parameters move into the …


Communication Based Control For Dc Microgrids, Mahmoud S. Saleh, Yusef Esa, Ahmed Mohamed Jan 2018

Communication Based Control For Dc Microgrids, Mahmoud S. Saleh, Yusef Esa, Ahmed Mohamed

Publications and Research

Centralized communication-based control is one of the main methods that can be implemented to achieve autonomous advanced energy management capabilities in DC microgrids. However, its major limitation is the fact that communication bandwidth and computation resources are limited in practical applications. This can be often improved by avoiding redundant communications and complex computations. In this paper, an autonomous communication-based hybrid state/event driven control scheme is proposed. This control scheme is hierarchical and heuristic, such that on the primary control level, it encompasses state-driven local controllers, and on the secondary control level, an event-driven MG centralized controller (MGCC) is used. This …


Improving Time-Of-Flight And Other Depth Images: Super-Resolution And Denoising Using Variational Methods, Salvador Canales Andrade Jan 2018

Improving Time-Of-Flight And Other Depth Images: Super-Resolution And Denoising Using Variational Methods, Salvador Canales Andrade

Open Access Theses & Dissertations

Depth information is a new important source of perception for machines, which allow them to have a better representation of the surroundings. The depth information provides a more precise map of the location of every object and surfaces in a space of interest in comparison with conventional cameras. Time of flight (ToF) cameras provide one of the techniques to acquire depth maps, however they produce low spatial resolution and noisy maps. This research proposes a framework to enhance and up-scale depth maps by using two different regularization terms: Total Generalized Variation (TGV) and Total Generalized Variation with a Structure Tensor …


Strong Stability Of A Class Of Difference Equations Of Continuous Time And Structured Singular Value Problem, Qian Ma, Keqin Gu, Narges Choubedar Jan 2018

Strong Stability Of A Class Of Difference Equations Of Continuous Time And Structured Singular Value Problem, Qian Ma, Keqin Gu, Narges Choubedar

SIUE Faculty Research, Scholarship, and Creative Activity

This article studies the strong stability of scalar difference equations of continuous time in which the delays are sums of a number of independent parameters tau_i, i = 1, 2, . . . ,K. The characteristic quasipolynomial of such an equation is a multilinear function of exp(-tau_i s). It is known that the characteristic quasipolynomial of any difference equation set in the form of one-delayper- scalar-channel (ODPSC) model is also in such a multilinear form. However, it is shown in this article that some multilinear forms of quasipolynomials are not characteristic quasipolynomials of any ODPSC difference equation set. The equivalence …


Strong Stability Of A Class Of Difference Equations Of Continuous Time And Structured Singular Value Problem, Qian Ma, Keqin Gu, Narges Choubedar Jan 2018

Strong Stability Of A Class Of Difference Equations Of Continuous Time And Structured Singular Value Problem, Qian Ma, Keqin Gu, Narges Choubedar

SIUE Faculty Research, Scholarship, and Creative Activity

This article studies the strong stability of scalar difference equations of continuous time in which the delays are sums of a number of independent parameters τi, i = 1, 2, . . . , K. The characteristic quasipolynomial of such an equation is a multilinear function of e−τis. It is known that the characteristic quasipolynomial of any difference equation set in the form of one-delay-per-scalar-channel (ODPSC) model is also in such a multilinear form. However, it is shown in this article that some multilinear forms of quasipolynomials are not characteristic quasipolynomials of any ODPSC difference equation set. The equivalence between …


Fundamentals Of Neutrosophic Logic And Sets And Their Role In Artificial Intelligence (Fundamentos De La Lógica Y Los Conjuntos Neutrosóficos Y Su Papel En La Inteligencia Artificial ), Florentin Smarandache, Maykel Leyva-Vazquez Jan 2018

Fundamentals Of Neutrosophic Logic And Sets And Their Role In Artificial Intelligence (Fundamentos De La Lógica Y Los Conjuntos Neutrosóficos Y Su Papel En La Inteligencia Artificial ), Florentin Smarandache, Maykel Leyva-Vazquez

Branch Mathematics and Statistics Faculty and Staff Publications

Neutrosophy is a new branch of philosophy which studies the origin, nature and scope of neutralities. This has formed the basis for a series of mathematical theories that generalize the classical and fuzzy theories such as the neutrosophic sets and the neutrosophic logic. In the paper, the fundamental concepts related to neutrosophy and its antecedents are presented. Additionally, fundamental concepts of artificial intelligence will be defined and how neutrosophy has come to strengthen this discipline.


High-Order Integral Equation Methods For Quasi-Magnetostatic And Corrosion-Related Field Analysis With Maritime Applications, Robert Pfeiffer Jan 2018

High-Order Integral Equation Methods For Quasi-Magnetostatic And Corrosion-Related Field Analysis With Maritime Applications, Robert Pfeiffer

Theses and Dissertations--Electrical and Computer Engineering

This dissertation presents techniques for high-order simulation of electromagnetic fields, particularly for problems involving ships with ferromagnetic hulls and active corrosion-protection systems.

A set of numerically constrained hexahedral basis functions for volume integral equation discretization is presented in a method-of-moments context. Test simulations demonstrate the accuracy achievable with these functions as well as the improvement brought about in system conditioning when compared to other basis sets.

A general method for converting between a locally-corrected Nyström discretization of an integral equation and a method-of-moments discretization is presented next. Several problems involving conducting and magnetic-conducting materials are solved to verify the accuracy …


Particle Filters For State Estimation Of Confined Aquifers, Graeme Field Jan 2018

Particle Filters For State Estimation Of Confined Aquifers, Graeme Field

UNF Graduate Theses and Dissertations

Mathematical models are used in engineering and the sciences to estimate properties of systems of interest, increasing our understanding of the surrounding world and driving technological innovation. Unfortunately, as the systems of interest grow in complexity, so to do the models necessary to accurately describe them. Analytic solutions for problems with such models are provably intractable, motivating the use of approximate yet still accurate estimation techniques. Particle filtering methods have emerged as a popular tool in the presence of such models, spreading from its origins in signal processing to a diverse set of fields throughout engineering and the sciences including …


Underwater Acoustic Signal Analysis Toolkit, Kirk Bienvenu Jr Dec 2017

Underwater Acoustic Signal Analysis Toolkit, Kirk Bienvenu Jr

LSU New Orleans Theses and Dissertations

This project started early in the summer of 2016 when it became evident there was a need for an effective and efficient signal analysis toolkit for the Littoral Acoustic Demonstration Center Gulf Ecological Monitoring and Modeling (LADC-GEMM) Research Consortium. LADC-GEMM collected underwater acoustic data in the northern Gulf of Mexico during the summer of 2015 using Environmental Acoustic Recording Systems (EARS) buoys. Much of the visualization of data was handled through short scripts and executed through terminal commands, each time requiring the data to be loaded into memory and parameters to be fed through arguments. The vision was to develop …


Food Web Control And Synchronization Using A Robust Feedback, Hector Puebla, Mariana Rodriguez-Jara, Cesar S. Lopez-Monsalvo, Eliseo Hernandez-Martinez, Alejandra Velasco-Perez Oct 2017

Food Web Control And Synchronization Using A Robust Feedback, Hector Puebla, Mariana Rodriguez-Jara, Cesar S. Lopez-Monsalvo, Eliseo Hernandez-Martinez, Alejandra Velasco-Perez

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.


Numerical Methods For Nonlinear Optimal Control Problems And Their Applications In Indoor Climate Control, Runxin He Aug 2017

Numerical Methods For Nonlinear Optimal Control Problems And Their Applications In Indoor Climate Control, Runxin He

McKelvey School of Engineering Graduate Student Theses & Dissertations

Efficiency, comfort, and convenience are three major aspects in the design of control systems for residential Heating, Ventilation, and Air Conditioning (HVAC) units. In this dissertation, we study optimization-based algorithms for HVAC control that minimizes energy consumption while maintaining a desired temperature, or even human comfort in a room. Our algorithm uses a Computer Fluid Dynamics (CFD) model, mathematically formulated using Partial Differential Equations (PDEs), to describe the interactions between temperature, pressure, and air flow. Our model allows us to naturally formulate problems such as controlling the temperature of a small region of interest within a room, or to control …


Information Theoretic Study Of Gaussian Graphical Models And Their Applications, Ali Moharrer Aug 2017

Information Theoretic Study Of Gaussian Graphical Models And Their Applications, Ali Moharrer

LSU Doctoral Dissertations

In many problems we are dealing with characterizing a behavior of a complex stochastic system or its response to a set of particular inputs. Such problems span over several topics such as machine learning, complex networks, e.g., social or communication networks; biology, etc. Probabilistic graphical models (PGMs) are powerful tools that offer a compact modeling of complex systems. They are designed to capture the random behavior, i.e., the joint distribution of the system to the best possible accuracy. Our goal is to study certain algebraic and topological properties of a special class of graphical models, known as Gaussian graphs. First, …


Measuring The Reflection Matrix Of A Rough Surface, Kenneth W. Burgi, Michael A. Marciniak, Mark E. Oxley, Stephen E. Nauyoks May 2017

Measuring The Reflection Matrix Of A Rough Surface, Kenneth W. Burgi, Michael A. Marciniak, Mark E. Oxley, Stephen E. Nauyoks

Faculty Publications

Phase modulation methods for imaging around corners with reflectively scattered light required illumination of the occluded scene with a light source either in the scene or with direct line of sight to the scene. The RM (reflection matrix) allows control and refocusing of light after reflection, which could provide a means of illuminating an occluded scene without access or line of sight. Two optical arrangements, one focal-plane, the other an imaging system, were used to measure the RM of five different rough-surface reflectors. Intensity enhancement values of up to 24 were achieved. Surface roughness, correlation length, and slope were examined …


P26. Global Exponential Stabilization On So(3), Soulaimane Berkane Mar 2017

P26. Global Exponential Stabilization On So(3), Soulaimane Berkane

Western Research Forum

Global Exponential Stabilization on SO(3)


Autonomous Quadrotor Collision Avoidance And Destination Seeking In A Gps-Denied Environment, Thomas C. Kirven Jan 2017

Autonomous Quadrotor Collision Avoidance And Destination Seeking In A Gps-Denied Environment, Thomas C. Kirven

Theses and Dissertations--Mechanical and Aerospace Engineering

This thesis presents a real-time autonomous guidance and control method for a quadrotor in a GPS-denied environment. The quadrotor autonomously seeks a destination while it avoids obstacles whose shape and position are initially unknown. We implement the obstacle avoidance and destination seeking methods using off-the-shelf sensors, including a vision-sensing camera. The vision-sensing camera detects the positions of points on the surface of obstacles. We use this obstacle position data and a potential-field method to generate velocity commands. We present a backstepping controller that uses the velocity commands to generate the quadrotor's control inputs. In indoor experiments, we demonstrate that the …


Compressive Vector Reconstruction: Hypothesis For Blind Image Deconvolution, Alonso Orea Amador Jan 2017

Compressive Vector Reconstruction: Hypothesis For Blind Image Deconvolution, Alonso Orea Amador

Open Access Theses & Dissertations

Alternative imaging devices propose to acquire and compress images simultaneously. These devices are based on the compressive sensing (CS) theory. A reduction in the measurement required for reconstruction without a post-compression sub-system allows imaging devices to become simpler, smaller, and cheaper. In this research, we propose a new algorithm to compress and reconstruct blurred images for CS imaging devices. Blur effect in images is common due to relative motion, lens, limited aperture dimensions, lack of focus, and/or atmospheric turbulence. Our intention is to compress a blurred image with CS techniques and then reconstruct a blur-free version using the proposed algorithm. …


A New Formulation Of Time Boundary Integral Equation For Acoustic Wave Scattering In The Presence Of A Uniform Mean Flow, Fang Q. Hu, Michelle E. Pizzo, Douglas M. Nark Jan 2017

A New Formulation Of Time Boundary Integral Equation For Acoustic Wave Scattering In The Presence Of A Uniform Mean Flow, Fang Q. Hu, Michelle E. Pizzo, Douglas M. Nark

Mathematics & Statistics Faculty Publications

It has been well-known that under the assumption of a constant uniform mean flow, the acoustic wave propagation equation can be formulated as a boundary integral equation, in both the time domain and the frequency domain. Compared with solving partial differential equations, numerical methods based on the boundary integral equation have the advantage of a reduced spatial dimension and, hence, requiring only a surface mesh. However, the constant uniform mean flow assumption, while convenient for formulating the integral equation, does not satisfy the solid wall boundary condition wherever the body surface is not aligned with the uniform mean flow. In …


Robust Feedback Control Based On Low Order Models With Uncertainty Estimation For A Class Of Biomedical Problems, Hector Puebla, Miguel A. Gutierrez-Limon, Eliseo Hernandez-Martinez, Alejandra Velasco-Perez Oct 2016

Robust Feedback Control Based On Low Order Models With Uncertainty Estimation For A Class Of Biomedical Problems, Hector Puebla, Miguel A. Gutierrez-Limon, Eliseo Hernandez-Martinez, Alejandra Velasco-Perez

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.


Performance-Robust Dynamic Feedback Control Of Lipschitz Nonlinear Systems, Winston Baker Oct 2016

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 …


Delay-Independent Stability Analysis Of Linear Time-Delay Systems Based On Frequency, Xianwei Li, Huijun Gao, Keqin Gu Aug 2016

Delay-Independent Stability Analysis Of Linear Time-Delay Systems Based On Frequency, Xianwei Li, Huijun Gao, Keqin Gu

SIUE Faculty Research, Scholarship, and Creative Activity

This paper studies strong delay-independent stability of linear time-invariant systems. It is known that delay-independent stability of time-delay systems is equivalent to some frequency-dependent linear matrix inequalities. To reduce or eliminate conservatism of stability criteria, the frequency domain is discretized into several sub-intervals, and piecewise constant Lyapunov matrices are employed to analyze the frequency-dependent stability condition. Applying the generalized Kalman–Yakubovich–Popov lemma, new necessary and sufficient criteria are then obtained for strong delay-independent stability of systems with a single delay. The effectiveness of the proposed method is illustrated by a numerical example.


An Interactive Likelihood For The Multi-Bernoulli Filter, Anthony B. Hoak Jul 2016

An Interactive Likelihood For The Multi-Bernoulli Filter, Anthony B. Hoak

Master's Theses (2009 -)

In this thesis, a simple yet effective technique is presented for increasing the accuracy of multi-target tracking algorithms with a focus on sequential Monte-Carlo implementations of random finite set-based approaches. This technique, referred to throughout this work as an interactive likelihood, exploits the spatial information that exists in any given measurement, reducing the need for data association and allowing for more target interaction thereby increasing overall tracking accuracy. The interactive likelihood is constructed entirely within the random finite set framework and is integrated with a multi-Bernoulli filter. In addition, a state-of-the-art deep neural network for pedestrian detection is combined in …


A General Framework Of Large-Scale Convex Optimization Using Jensen Surrogates And Acceleration Techniques, Soysal Degirmenci May 2016

A General Framework Of Large-Scale Convex Optimization Using Jensen Surrogates And Acceleration Techniques, Soysal Degirmenci

McKelvey School of Engineering Graduate Student Theses & Dissertations

In a world where data rates are growing faster than computing power, algorithmic acceleration based on developments in mathematical optimization plays a crucial role in narrowing the gap between the two. As the scale of optimization problems in many fields is getting larger, we need faster optimization methods that not only work well in theory, but also work well in practice by exploiting underlying state-of-the-art computing technology.

In this document, we introduce a unified framework of large-scale convex optimization using Jensen surrogates, an iterative optimization method that has been used in different fields since the 1970s. After this general treatment, …


Acoustic Firearm Discharge Detection And Classification In An Enclosed Environment, Lorenzo Luzi, Eric Gonzalez, Paul Bruillard, Matthew Prowant, James Skorpik, Michael Hughes, Scott Child, Duane Kist, John E. Mccarthy May 2016

Acoustic Firearm Discharge Detection And Classification In An Enclosed Environment, Lorenzo Luzi, Eric Gonzalez, Paul Bruillard, Matthew Prowant, James Skorpik, Michael Hughes, Scott Child, Duane Kist, John E. Mccarthy

Mathematics Faculty Research

Two different signal processing algorithms are described for detection and classification of acoustic signals generated by firearm discharges in small enclosed spaces. The first is based on the logarithm of the signal energy. The second is a joint entropy. The current study indicates that a system using both signal energy and joint entropy would be able to both detect weapon discharges and classify weapon type, in small spaces, with high statistical certainty.


Supervised Learning-Based Explicit Nonlinear Model Predictive Control And Unknown Input Estimation In Biomedical Systems, Ankush Chakrabarty Feb 2016

Supervised Learning-Based Explicit Nonlinear Model Predictive Control And Unknown Input Estimation In Biomedical Systems, Ankush Chakrabarty

Open Access Dissertations

Application of nonlinear control theory to biomedical systems involves tackling some unique and challenging problems. The mathematical models that describe biomedical systems are typically large and nonlinear. In addition, biological systems exhibit dynamics which are not reflected in the model (so-called 'un-modeled dynamics') and hard constraints on the states and control actions, which exacerbate the difficulties in designing model-based controllers or observers.

This thesis investigates the design of scalable fast explicit nonlinear model predictive controllers (ENMPCs). The design involves (i) the estimation of a feasible region using Lyapunov stability methods and support vector machines; and (ii) within the estimated feasible …


Signal Flow Graph Approach To Efficient Dst I-Iv Algorithms, Sirani M. Perera Jan 2016

Signal Flow Graph Approach To Efficient Dst I-Iv Algorithms, Sirani M. Perera

Publications

In this paper, fast and efficient discrete sine transformation (DST) algorithms are presented based on the factorization of sparse, scaled orthogonal, rotation, rotation-reflection, and butterfly matrices. These algorithms are completely recursive and solely based on DST I-IV. The presented algorithms have low arithmetic cost compared to the known fast DST algorithms. Furthermore, the language of signal flow graph representation of digital structures is used to describe these efficient and recursive DST algorithms having (n�1) points signal flow graph for DST-I and n points signal flow graphs for DST II-IV.