Electrical and Computer Engineering Commons^™

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 between local strong ...

Recursive Non-Local Means Filter For Video Denoising, Redha A. Ali, Russell C. Hardie

Electrical and Computer Engineering Faculty Publications

In this paper, we propose a computationally efficient algorithm for video denoising that exploits temporal and spatial redundancy. The proposed method is based on non-local means (NLM). NLM methods have been applied successfully in various image denoising applications. In the single-frame NLM method, each output pixel is formed as a weighted sum of the center pixels of neighboring patches, within a given search window.

The weights are based on the patch intensity vector distances. The process requires computing vector distances for all of the patches in the search window. Direct extension of this method from 2D to 3D, for video ...

Sensor-Based Legged Robot Homing Using Range-Only Target Localization, Vasileios Vasilopoulos, Omur Arslan, Avik De, Daniel E. Koditschek

Departmental Papers (ESE)

This paper demonstrates a fully sensor-based reactive homing behavior on a physical quadrupedal robot, using onboard sensors, in simple (convex obstacle-cluttered) unknown, GPS-denied environments. Its implementation is enabled by our empirical success in controlling the legged machine to approximate the (abstract) unicycle mechanics assumed by the navigation algorithm, and our proposed method of range-only target localization using particle filters.

For more information: Kod*lab

Answering Food Insecurity: Serving The Community With Food And Knowledge Using Technology, Courtney Simpson

Purdue Journal of Service-Learning and International Engagement

The courses of Tech120, CGT110, and ENGT 180/181 and Red Gold at Purdue collaborated to design a robot that would plant and water a garden for a local community charter school. The students centered the project on the users’ needs for fresh food, nutrition education, and early exposure to STEM for children. The school, Anderson Preparatory Academy (APA), is comprised of many children who come from low-income families and are in the free or reduced lunch program. Inspired from “Farm Bot,” a similar system that allows for almost hands-free gardening, the “Boiler Bot” is designed to be scalable so ...

Co-Existence Of Microbial Ecology In A Chemostat Using A Robust Feedback, Hector Puebla, Mariana Rodriguez-Jara, Margarita M. Gonzalez-Brambila, Eliseo Hernandez-Martinez, Alejandra Velasco-Perez, Ennio Piceno-Diaz

Annual Symposium on Biomathematics and Ecology: Education and Research

No abstract provided.

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.

Learning And Control Using Gaussian Processes, Achin Jain, Truong X Nghiem, Manfred Morari, Rahul Mangharam

Real-Time and Embedded Systems Lab (mLAB)

Building physics-based models of complex physical systems like buildings and chemical plants is extremely cost and time prohibitive for applications such as real-time optimal control, production planning and supply chain logistics. Machine learning algorithms can reduce this cost and time complexity, and are, consequently, more scalable for large-scale physical systems. However, there are many practical challenges that must be addressed before employing machine learning for closed-loop control. This paper proposes the use of Gaussian Processes (GP) for learning control-oriented models: (1) We develop methods for the optimal experiment design (OED) of functional tests to learn models of a physical system ...

Performance And Mitigation Strategy Of Distributed Ac-Stacked Pv Inverter Architecture Under Grid Background Harmonics, Namwon Kim, Hamidreza Jafarian, Babak Parkhideh, Johan Enslin

Hamidreza Jafarian

A Distributed Active And Reactive Power Control For Grid-Tied Cascaded H-Bridge Pv Inverter System Using Relative Gain Array Approach, Hamidreza Jafarian, Namwon Kim, Babak Parkhideh

Hamidreza Jafarian

An Overview Of The Usage Of Default Passwords, Brandon Knierem, Xiaolu Zhang, Philip Levine, Frank Breitinger, Ibrahim Baggili

Electrical & Computer Engineering and Computer Science Faculty Publications

The recent Mirai botnet attack demonstrated the danger of using default passwords and showed it is still a major problem. In this study we investigated several common applications and their password policies. Specifically, we analyzed if these applications: (1) have default passwords or (2) allow the user to set a weak password (i.e., they do not properly enforce a password policy). Our study shows that default passwords are still a significant problem: 61% of applications inspected initially used a default or blank password. When changing the password, 58% allowed a blank password, 35% allowed a weak password of 1 ...

A Parameterized Simulation Of Doppler Lidar, David B. Chester

All Graduate Theses and Dissertations

Upcoming missions to explore planetary bodies in the solar system will require accurate position and velocity data during descent in order to land safely at a predesignated site. A Doppler lidar instrument could provide measurements of the altitude, attitude, and velocity of the landing vehicle to supplement the data collected by other instruments. A flexible simulation tool would aid the tasks of designing and testing the functionality of such an instrument.

LadarSIM is a robust parameterized simulation tool developed for time of flight lidar at Utah State University's Center for Advanced Imaging Ladar. This thesis outlines how LadarSIM was ...

Design Of Dc-Link Vscf Ac Electrical Power System For The Embraer 190/195 Aircraft, Eduardo Francis Carvalho Freitas, Nihad E. Daidzic,

Journal of Aviation Technology and Engineering

A proposed novel DC-Link VSCF AC-DC-AC electrical power system converter for Embraer 190/195 transport category airplane is presented. The proposed converter could replace the existing conventional system based on the CSCF IDGs. Several contemporary production airplanes already have VSCF as a major or backup source of electrical power. Problems existed with the older VSCF systems in the past; however, the switched power electronics and digital controllers have matured and can be now, in our opinion, safely integrated and replace existing constant-speed hydraulic transmissions powering CSCF AC generators. IGBT power transistors for medium-level power conversion and relatively fast efficient switching ...

Visual Multiple Target Tracking From A Descending Aerial Platform, Parker C. Lusk, Randal Beard

All Student Publications

A real-time visual multiple target tracker is demonstrated onboard a descending multirotor. Measurements of moving ground targets are generated using the Kanade-Lucas-Tomasi (KLT) tracking method. Homography-based image registration is used to align the measurements into the same coordinate frame, allowing for the detection of independently moving objects. The recently developed Recursive-RANSAC algorithm uses the visual measurements to estimate targets in clutter. Altitude-dependent tuning increases track continuity and coverage during the descent of the vehicle. The algorithm requires no operator interaction and increases the situation awareness of the unmanned aerial system. Real-time tracking efficiency is analyzed on GPUs and CPUs. Tracking ...

Residual Self-Interference Cancellation And Data Detection In Full-Duplex Communication Systems, Abbas Koohian, Hani Mehrpouyan, Ali Arshad Nasir, Salman Durrani, Steven D. Blostein

Hani Mehrpouyan

Residual self-interference cancellation is an important practical requirement for realizing the full potential of full-duplex (FD) communication. Traditionally, the residual selfinterference is cancelled via digital processing at the baseband, which requires accurate knowledge of channel estimates of the desired and self-interference channels. In this work, we consider point-to-point FD communication and propose a superimposed signaling technique to cancel the residual self-interference and detect the data without estimating the unknown channels. We show that when the channel estimates are not available, data detection in FD communication results in ambiguity if the modulation constellation is symmetric around the origin. We demonstrate that ...

Relative Target Estimation Using A Cascade Of Extended Kalman Filters, Jerel Nielsen, Randal Beard

All Student Publications

This paper presents a method of tracking multiple ground targets from an unmanned aerial vehicle (UAV) in a 3D reference frame. The tracking method uses a monocular camera and makes no assumptions on the shape of the terrain or the target motion. The UAV runs two cascaded estimators. The first is an Extended Kalman Filter (EKF), which is responsible for tracking the UAV’s state, such as position and velocity relative to a fixed frame. The second estimator is an EKF that is responsible for estimating a fixed number of landmarks within the camera’s field of view. Landmarks are ...

Fusing Self-Reported And Sensor Data From Mixed-Reality Training, Trevor Richardson, Stephen B. Gilbert, Joseph Holub, Frederick Thompson, Anastacia Macallister, Rafael Radkowski, Eliot Winer

Anastacia MacAllister

Military and industrial use of smaller, more accurate sensors are allowing increasing amounts of data to be acquired at diminishing costs during training. Traditional human subject testing often collects qualitative data from participants through self-reported questionnaires. This qualitative information is valuable but often incomplete to assess training outcomes. Quantitative information such as motion tracking data, communication frequency, and heart rate can offer the missing pieces in training outcome assessment. The successful fusion and analysis of qualitative and quantitative information sources is necessary for collaborative, mixed-reality, and augmented-reality training to reach its full potential. The challenge is determining a reliable framework ...

Data Predictive Control Using Regression Trees And Ensemble Learning, Achin Jain, Francesco Smarra, Rahul Mangharam

Real-Time and Embedded Systems Lab (mLAB)

Decisions on how to best operate large complex plants such as natural gas processing, oil refineries, and energy efficient buildings are becoming ever so complex that model-based predictive control (MPC) algorithms must play an important role. However, a key factor prohibiting the widespread adoption of MPC, is the cost, time, and effort associated with learning first-principles dynamical models of the underlying physical system. An alternative approach is to employ learning algorithms to build black-box models which rely only on real-time data from the sensors. Machine learning is widely used for regression and classification, but thus far data-driven models have not ...

Further Cost Reduction Of Battery Manufacturing, Amir A. Asif, Rajendra Singh

Amir Asif

The demand for batteries for energy storage is growing with the rapid increase in photovoltaics (PV) and wind energy installation as well as electric vehicle (EV), hybrid electric vehicle (HEV) and plug-in hybrid electric vehicle (PHEV). Electrochemical batteries have emerged as the preferred choice for most of the consumer product applications. Cost reduction of batteries will accelerate the growth in all of these sectors. Lithium-ion (Li-ion) and solid-state batteries are showing promise through their downward price and upward performance trends. We may achieve further performance improvement and cost reduction for Li-ion and solid-state batteries through reduction of the variation in ...

Emerging Role Of Photovoltaics For Sustainably Powering Underdeveloped, Emerging, And Developed Economies, Rajendra Singh, Amir A. Asif, Ganesh K. Venayagamoorthy, Akhlesh Lakhtakia, Mahmoud Abdelhamid, Githin F. Alapatt, David A. Ladner

Amir Asif

With the advent of low-cost solar photovoltaic (PV) panels and our ability to generate, store, and use electrical energy locally without the need for long-range transmission, the world is about to witness transformational changes in electricity infrastructures. The use of DC electricity enhances systemwide efficiency. DC microgrids and nanogrids powered by solar PV systems and gigawatt batteries for electricity storage can sustainably power the needs of all human beings equitably and empower every individual. Ultralarge-scale manufacturing of PV systems and batteries, a vertically integrated business model, and a targeted monetary policy of quantitative easing can rapidly power all human activities.

Technical And Economic Assessment Of Perovskite Solar Cells For Large Scale Manufacturing, Amir A. Asif, Rajendra Singh, Githin F. Alapatt

Amir Asif

In this paper, we have carried out detailed technical and economic assessment of perovskite solar cells for large scale manufacturing. For ultra-small area of the order of 0.1 cm², efficiency of 20% or so are reported. However, for area of 25 cm², the efficiency is about 10%. Based on the photovoltaic module manufacturing requirements of no constraint on the supply of raw materials, low variability of every key process and process-induced defects, low cost of manufacturing, prospects for further cost reduction in the future, green manufacturing, and long-term reliability, there are absolutely no prospects of manufacturing perovskite ...