Volume 13 | Issue 2 | June 2016 www.ajuronline.org Print Edition ISSN 1536-4585 Online Edition ISSN 2375-8732 Volume 13 | Issue 2 | June 2016 www.ajuronline.org 2 AJUR History and Editorial Board 3 Special Thanks to AJUR’s Sponsors 5 Robust Nonlinear Control of BLDC Motor in Quadcopter Applications Steven T. Elliott & Thomas W. Carr 15 Development of Four-Square Fiducial Markers for Analysis of Paper Analytical Devices Jenna Wilson, Tabitha Ricketts, Ian Bentley & Ewa Misiolek 29 Sensitivity Analysis of Common Input Parameters in Tools for Modeling Energy in Homes Sheikh Tijan Tabban & Nelson Fumo 43 Feeding Anti-Semitism: Representations of Jewish Food Practices in Der ewige Jude Forrest Picher 57 hTERT Suppression via Small Interference RNA in Cervical Cancer Cells Shawn Gray & Douglas Christensen 65 Malate : Quinone Oxidoreductase and Malic Enzyme are required for the Plant Pathogen Pseudomonas syringae pv. tomato DC3000 to Utilize Malate Zabrina Ebert, Preston Jacob, Katrina Jose, Lina Fouad, Katherine Vercellino, Steven Van Dorn, Mahaa Sidiqqi & Eve M. Mellgren 73 Engaging Students in Science through a Nature Hike: A Case of Two Students with ADHD Ashleigh Moore, Kristy Lynn Daniel & Aimée K. Thomas 81 Evaluation of Antiulcer Activity of Laghusoothshekhar (an Ayurvedic Formula) in Pyloric Ligature Induced Gastric Ulcers in Albino Rats Nilofer Sayed & Vandana Barve 87 Using Statistical Approaches to Model Natural Disasters Audrene S. Edwards & Kumer Pial Das 105 Explicit Solution for Cylindrical Heat Conduction Kaitlyn Parsons, Tyler Reichanadter, Andi Vicksman & Harvey Segur 1 American Journal of Undergraduate Research www.ajuronline.org American Journal of Undergraduate Research (AJUR) is a national, peer-reviewed, open-source, quarterly, multidisciplinary student research journal. It is indexed internationally by EBSCO, and is listed via the Library of Congress under ISSNs of 1536-4585 (for print) and 2375-8732 (for web). The journal was established in 2002. EDITORIAL TEAM Volume 13 | Issue 2 | June 2016 Dr. Kestutis G. 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Cashman, Dr. Mark Baker, [email protected] [email protected] ENGINEERING, MANUFACTURING AND CONSTRUCTION, ROBOTICS Dr. Haoyu Wang, [email protected] Volume 13 | Issue 2 | June 2016 2 American Journal of Undergraduate Research www.ajuronline.org SPECIAL THANKS AJUR is made possible through the assistance of our sponsors. Support for this issue has been provided by Wiley as well as the Office of the Provost at the State University of New York at Oswego. Thank you! Interested in supporting quality undergraduate research? Request sponsorship information at [email protected] Volume 13 | Issue 2 | June 2016 3 American Journal of Undergraduate Research www.ajuronline.org Volume 13 | Issue 2 | June 2016 4 American Journal of Undergraduate Research www.ajuronline.org Robust Nonlinear Control of BLDC Motor in Quadcopter Applications Steven T. Elliott and Thomas W. Carr Department of Mathematics, Southern Methodist University, Dallas, TX Student: [email protected] Mentor: [email protected] ABSTRACT This paper describes the development of a nonlinear closed loop motor control system for a quadcopter micro-unmanned aerial vehicle (micro-UAV) platform. Research groups have analyzed the performance of brushless direct current (BLDC) motors with nonlinear effects in various applications, focusing on areas such as friction’s effect on position. This paper analyzes the nonlinear effects of BLDC motors on speed when these motors are used in quadcopter flying robots. Notably, to account for nonlinear torque from the aerodynamic forces on a quadcopter rotor, a Control Lyapunov Function (CLF) approach is used in designing a stable feedback control system. The paper also explains the custom model and simulation of the system built in MATLAB/Simulink used to demonstrate and quantify the successful performance of the design. KEYWORDS Control Lyapunov Function; Micro-Unmanned Aerial Vehicle; Aerial Robotics; Quadcopters; Nonlinear Motor Control INTRODUCTION One area of research and development that has enormous potential is the multicopter micro-UAV. This flying robot typically uses four propellers, one mounted on each of the four ends of a cross-shaped frame as shown in Figure 1. Two propellers lying opposite to each other both rotate clockwise, and the other pair rotates counterclockwise, canceling the torques. Pitch, roll, and yaw movements are achieved by varying the speed of the motors; the robot carries an onboard controller and battery as well. 1 Quadcopters range in size as small as 6 centimeters from tip to tip and 3 grams in weight.2 Figure 1. A quadcopter micro-UAV. With their vertical flight and hover abilities, durability, and ease of use both indoors and outdoors, quadcopters are growing in popularity and have many promising applications, either as individual vehicles or in cooperation with others.2–5 Some of the uses include search and rescue, surveillance, exploration, photography, transport, and construction; quadcopters can be particularly helpful in environments that are inaccessible, contaminated, or otherwise dangerous.6, 7 The performance of the quadcopter depends on the speed of response of the motors in achieving controlled, stable flight. Research groups studying quadcopters often assume unchanging aerodynamics, but quadcopters experience significant aerodynamic disturbance effects due to their surroundings, complex interactions with multiple UAVs or, at small scales, even to mild wind gusts.7, 8 Researchers often deal with these by reducing the speed, keeping greater distance between the quadcopter and its surroundings, using simpler trajectories, attempting to limit the roll and pitch angles, and controlling the environment.2 Volume 13 | Issue 2 | June 2016 5 American Journal of Undergraduate Research www.ajuronline.org Quadcopters are poised to ecoe a idely used technology, an improements in uadcopter controls could have a significant ince , the , are ector fiels in . pecifically, they are equations of the for impact on their efficacy. Researchers have taken many ifferent approaches to this control system design, summarized ell in References 6, . few of the techniues include ehicle control loops that use feedbac linearization for elocity and attitue 1, 2, control, proportional-integral-deriatie (PI control for attitue and position, a preictor-corrector algorithm for angular Equati . elocity control,4 sequences of controllale trajectories accoplishing ore complex aneuvers,5 iteratie learning,5 and a decentralized adaptie controller for attitue and altitue.9 Instead,
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