We aren't endorsed by this school 
Calvin  ENGR 315
 Calvin
 Unknown
 Network+ Guide to Networks (Networking (Course Technology)), ForeignExchangeRate Forecasting with Artificial Neural Networks (International Series in Operations Research & Management Science), Fundamentals of Neural Networks: Architectures, Algorithms And Applications, Neural Networks for Modelling and Control of Dynamic Systems: A Practitioner's Handbook (Advanced Textbooks in Control and Signal Processing), Neural Networks: An Introduction

Temperaturecontrol
School: Calvin
1 A Study On PID Temperature Control For ENGR 315, Control Systems T. VanDerPuy, NonIEEE Member AbstractThis paper focuses on an in depth study of industrial temperature controllers, their use in a workplace environment, some terms and options as

Sixthsense
School: Calvin
Man's Sixth Sense M.E. Husson, Senior Student at Calvin College Abstract A car that controls its self is a marvel. Naturally, one of the best ways to control the car is with a control system. The car is driven by differential steering meaning that

Presentation
School: Calvin
Feedback of Biological Systems Specifically Humans Ryan Bussis Samuel Stearley Introduction Tracking Balance Movement: Walking/Swimming Modeling Vestibular Sensors in Ear These are spaces in the ear filled with a liquid that moves across hairs.

Mechanicalgovernor
School: Calvin
Controlling Speed Mechanically Engr 315 Control Systems Calvin College 8 December 2004 Brian Katerberg Andy Vander Moren The Original Governor James Watt's Flyball Governor Used to prevent steam engines from overheating while responding to the ap

Flight Controls
School: Calvin
1 Flight Control Dynamics and Unmanned Aerial Vehicles Kevin D. Palmer Calvin College, Grand Rapids, MI 49546 Unmanned Aerial Vehicles (UAVs) was evident in the Vietnam War, where 544 of them went down [4], and this was only a fraction of the 3000 p

PID Tuning MethodsAutomation Study With MathCada
School: Calvin
PID Tuning Methods An Automatic PID Tuning Study with MathCad Neil Kuyvenhoven Calvin College ENGR. 315 December 19, 2002 Abstract There are several methods for tuning a PID controller. This paper takes a qualitative look at three common methods, wi

PID Temperature Controller
School: Calvin
PID Temperature Controller Allen Bradley 1771TCM Brian Van Eyk Background Applications Plastic injection molding Powder paint There is a need for quick and accurate temperature control Two solutions Sensor with simple logic controller Smart

NNSystems And Power Systems
School: Calvin
Power Systems Application of Artificial Neural Networks. (ANN) Introduction Brief history. Structure How they work Sample Simulations. (EasyNN) Why use them (Merits and Demerits)? Current Applications NN & Power Systems Conclusion Introductio

NNSimulations
School: Calvin
Figure 5: Simulating a current transformer in simpowersystems. Figure 6: Current transformer during normal operation with primary voltage and secondary current superimposed on each other. 6 Figure 7: Current transformer showing effect of power sat

Daylight Harvesting On
School: Calvin
Effects of Daylight Harvesting on Electronic Lighting Control Copyright 2004 Joshua Scot Lester  Calvin College Engineering 315 Control Systems Triac Dimming Zerocrossing A dimmer controls the power to the load through a solid state switch or tri

ControllingWonderland
School: Calvin
1 Controlling Wonderland (Dec. 2003) Michael J. Bloem and Samuel L. Schoofs, Student Member, IEEE paper will evaluate the role of pollution taxes in achieving sustainable development. II. DESCRIPTION OF PREVIOUS WORK A. The Wonderland Model The Wond

315 Presentationkenmorgan
School: Calvin
Fuzzy Logic Control Systems Ken Morgan ENGR 315 December 5, 2001 What is Fuzzy Logic? Fuzzy logic allows any value between 0 and 1. Fuzzy logic is a superset of Boolean logic. Fuzzy logic allows half truths such as: "The cup is both half full and

Lab4
School: Calvin
ENGR 315 MATLAB / SIMULINK  Laboratory # 4 Mathematical Models of Systems Objectives: Study the performance of Feedback Control Systems. Effects of a third pole on the secondorder system response. Equipment: Computer Lab PC Resources: 1  Modern Co

Lab1
School: Calvin
ENGR 315 MATLAB / SIMULINK  Laboratory # 1 Introduction to MATLAB / Simulink Objectives: 1 To help students to become familiar with MATLAB (Control Systems Toolbox) and Simulink simulation capabilities . 2  To practice the implementation of contro

Lab2handouta
School: Calvin
ENGR 315 CALVIN COLLEGE Engineering Department MATLAB / SIMULINK  Laboratory # 2 Mathematical Models of Systems Objectives: In this lab we consider some of the issues surrounding the modeling of physical systems. Equipment: Computer Lab PC Resour

Power_Systems_Audio_Enhanced
School: Calvin
*Audio Enhanced Presentation* Controls and Power Systems By David Ringle and Scott Rydbeck Dec. 10, 2003 Engr 315 Page 1 Outline How a Power Grid Works? PowerWorld PSCAD Control Systems Aspects Frequency and Load Dec. 10, 2003 Engr 315

Nn
School: Calvin
Introduction to Neural Network Justin Jansen December 9th 2002 Neural Network Definition of Artificial Neural Network Fundamental concepts Where they fit in a control system What they can do and where they fail Example pattern recognition Wha

315roboticarm
School: Calvin
1 Control Systems Overview for Automated Robotic Welding Machines D. A. Wykstra, Senior, Calvin College Engineering AbstractControl Systems are overviewed and discussed for two basic divisions of robotic welding machines. The small, single operati

Stamping Press
School: Calvin
1 Metal Stamping Press Load Sensing: Integration of Load Measurement in Press Control Systems Matthew De Kam Abstract Load monitoring in metal stamping presses has been an important method of measuring press performance for decades. This monitoring

Temperaturecontrolpid
School: Calvin
1 A Study On PID Temperature Control For ENGR 315, Control Systems T. VanDerPuy, NonIEEE Member AbstractThis paper focuses on an in depth study of industrial temperature controllers, their use in a workplace environment, some terms and options as

Chapter51
School: Calvin
Chapter 5 The Performance of Feedback Control Systems The ability to adjust the transient and steadystate response of a feedback control system is a beneficial outcome of the design of control systems. One of the first steps in the design process i

Chapter6
School: Calvin
Chapter 6 The Stability of Linear Feedback Systems The issue of ensuring the stability of a closedloop feedback system is central to control system design. Knowing that an unstable closedloop system is generally of no practical value, we seek meth

Lab5handouta
School: Calvin
ENGR 315 MATLAB / SIMULINK  Laboratory # 5 Mathematical Models of Systems Objectives: To learn about the Stability Criteria (HW Method) and Root Locus Method for designing and analyzing feedback control systems. Equipment: Computer Lab PC Resources

Lab1handout
School: Calvin
ENGR 315 MATLAB / SIMULINK  Laboratory # 1 Introduction to MATLAB / Simulink Objectives: 1 To help students to become familiar with MATLAB (Control Systems Toolbox) and Simulink simulation capabilities . 2  To practice the implementation of contro

Missilecontrols
School: Calvin
Missile Controls ENGR 315A Prof. P. Ribeiro Presented by: Craig Mulder Outline Afghanistan How do they do that? Types of Missile Controls Physical Controls Inertial Navigation System (INS) Global Positioning System (GPS) Terrain Contour Matchi

FuzzyPresentationkenmorgan
School: Calvin
Fuzzy Logic Control Systems Ken Morgan ENGR 315 December 5, 2001 What is Fuzzy Logic? Fuzzy logic allows any value between 0 and 1. Fuzzy logic is a superset of Boolean logic. Fuzzy logic allows half truths such as: "The cup is both half full and

Traction Control
School: Calvin
Traction Control Michael Boersma Michael LaGrand 12/10/03 Outline Methods for traction control Method studied Results Questions Traction Control Methods Control of power to wheels Control of breaks Factors used for control Velocity Yaw r

Phase Locked Loop Design
School: Calvin
Phase Locked Loop Design Matt Knoll Engineering 315 Introduction What is a PLL? Control System Representation Parts of a PLL PLL in Simulink What is a PLL? Digital frequency control system Generate high speed oscillations Acquire and track s

Neural Networks Presentation
School: Calvin
Neural Networks Sarah Ezzell Engr. 315 What Are They? Information processing system (nonalgorithmic, nondigital) Inspired by the human brain Made of artificial neurons (neurodes) Crude approximation of biological neurons Connected by weigh

Neural Network
School: Calvin
Neural Network Control of Power Systems. Patrick Avoke, Student Member, IEEE (Calvin College) Abstract: Like most other real world dynamical systems, power systems are nonlinear hence require a convenient method of controlling the activities of the

Genetic Algorithms
School: Calvin
Genetic Algorithms: An Examination of the Traveling Salesman Problem Troy Cok Engineering 315 December 3, 2001 Basic Overview o Genetic algorithms are attempts to model evolutionary behavior o Survival of the fittest, etc. o More than mere simulat

GPS Navigation With Kalman Filter Integration
School: Calvin
GPS/Dead Reckoning Navigation with Kalman Filter Integration Paul Bakker Kalman Filter "The Kalman Filter is an estimator for what is called the linearquadratic problem, which is the problem of estimating the instantaneous `state' of a li

GPSKalman
School: Calvin
1 Kalman Filter Fundamentals and Application to Global Position Systems and Inertial Navigation Systems Paul Bakker, Student Member IEEE, Student of Calvin College AbstractAn introduction to some of the errors present in the Global Positioning Sys

Fuzzy Logic And Fuzzy Control Systems
School: Calvin
FUZZY LOGIC AND FUZZY LOGIC SUN TRACKING CONTROL RYAN JOHNSON DECEMBER 17, 2002 CALVIN COLLEGE ENGR315A ABSTRACT: Fuzzy logic is a rulebased decision process that seeks to solve problems where the system is difficult to model and where ambiguity or

Cruise Control
School: Calvin
Cruise Control Karen Lie Engr 315 Outline Introduction to Cruise Control CC Modeling CC Simulation Introduction to Adaptive Control ACC Modeling ACC Simulation Cruise Control System Input: buttons on the steering wheel, brake, clutch, ga

Cruise Control2
School: Calvin
Cruise Control Andrew Huisjen Introduction Invented by Ralph Teetor Introduced as option on 1958 Chryslers Blind Engineer Didn't like the way his lawyer drove Got patent in 1945 Now installed on nearly 90% of new cars and truck System Co

ASD Presentation
School: Calvin
Adjustable Speed Drives Justin Voogt Engineering 315 ASD Basics What does an ASD do? ASD Components Regulator Process Control Converter/Rectifier AC DC AC Inverter DC Proportional Control ASD Regulator PID Control Proportional + Int

Lab5
School: Calvin
ENGR 315 MATLAB / SIMULINK  Laboratory # 5 Mathematical Models of Systems Objectives: Study the stability of linear feedback systems. Equipment: Computer Lab PC Resources: 1  Modern Control Systems, Dorf and Bishop 2  Modern Control Systems  Anal

Lab3
School: Calvin
ENGR 315 MATLAB / SIMULINK  Laboratory # 3 Mathematical Models of Systems Objectives: Study the characteristics of open and closedloop systems. Investigate the sensitivity to parameters variation, disturbance, stability and steadystate error. Equ

Lab3handouta
School: Calvin
ENGR 315 MATLAB / SIMULINK  Laboratory # 3 September 23, 2002 Mathematical Models of Systems Objectives: Study the characteristics of open and closedloop systems. Investigate the sensitivity to parameters variation, disturbance, stability and ste

Lab5handout
School: Calvin
ENGR 315 MATLAB / SIMULINK  Laboratory # 5 Mathematical Models of Systems Objectives: To learn about the Root Locus Method for designing and analyzing feedback control systems. Equipment: Computer Lab PC Resources: 1  Modern Control Systems, Dorf a

Lab4handout
School: Calvin
ENGR 315 MATLAB / SIMULINK  Laboratory # 4 Mathematical Models of Systems Objectives: Study the performance of Feedback Control Systems. Effects of a third pole on the secondorder system response. Equipment: Computer Lab PC Resources: 1  Modern Co

Lab2handout
School: Calvin
ENGR 315 CALVIN COLLEGE Engineering Department MATLAB / SIMULINK  Laboratory # 2  Mathematical Models of Systems Objectives: In this lab we consider some of the issues surrounding the modeling of physical systems. Equipment: Computer Lab PC Reso

Mptmpwzeta
School: Calvin
Relationship between Mpt (time domain) and Mpw (frequency domain) as a function of := 0.2, 0.21. 0.69  Mpt( ) := 1 + e 1 2 Mpt = function 1 2 Mpw( ) := 2 1  3 Mpw = function 2.5 Mpt ( ) Mpw ( ) 2 1.5 1 0.1 0.2 0.3 0.4 0.5

Lab22002f
School: Calvin
ENGR 315 CALVIN COLLEGE Engineering Department MATLAB / SIMULINK  Laboratory # 2  Mathematical Models of Systems Objectives: In this lab we consider some of the issues surrounding the modeling of physical systems. Equipment: Computer Lab PC, MAT

Lab4handouta
School: Calvin
ENGR 315 MATLAB / SIMULINK  Laboratory # 4 Mathematical Models of Systems Objectives: Study the performance of Feedback Control Systems. Effects of a third pole on the secondorder system response. Equipment: Computer Lab PC Resources: 1  Modern Co

Lab3handout
School: Calvin
ENGR 315 MATLAB / SIMULINK  Laboratory # 3 Mathematical Models of Systems Objectives: Study the characteristics of open and closedloop systems. Investigate the sensitivity to parameters variation, disturbance, stability and steadystate error. Equ

Lab6handout
School: Calvin
ENGR 315 MATLAB / SIMULINK  Laboratory # 6 Mathematical Models of Systems Objectives: To learn about frequency response methods for designing analyzing and control systems. Equipment: Computer Lab PC Resources: 1  Modern Control Systems, Dorf and

Lab6
School: Calvin
ENGR 315 MATLAB / SIMULINK  Laboratory # 6 Mathematical Models of Systems Objectives: To learn about the Root Locus Method for designing and analyzing feedback control systems. Equipment: Computer Lab PC Resources: 1  Modern Control Systems, Dorf a

Lab2
School: Calvin
ENGR 315 MATLAB / SIMULINK  Laboratory # 2 Mathematical Models of Systems Objectives: In this lab we continue to consider the issues surrounding the modeling and simulation of physical systems as we become familiar with the simulation tools and basi

Lab8
School: Calvin
ENGR 315 MATLAB / SIMULINK  Laboratory # 8 Mathematical Models of Systems Objectives: To learn about frequency response methods for designing analyzing and control systems. Equipment: Computer Lab PC Resources: 1  Modern Control Systems, Dorf and

Feedbackbilogicalsystems
School: Calvin
Feedback of Biological Systems Specifically Humans Ryan Bussis Samuel Stearley Introduction Tracking Balance Movement: Walking/Swimming Modeling Vestibular Sensors in Ear These are spaces in the ear filled with a liquid that moves across hairs.

Chapter7
School: Calvin
Chapter 7: The Root Locus Method In the preceding chapters we discussed how the performance of a feedback system can be described in terms of the location of the roots of the characteristic equation in the splane. We know that the response of a clos

Syllabus315f2004
School: Calvin
Calvin College Engineering Department Engineering 315  Control Systems Fall 2004 Professor: Paulo F. Ribeiro SB134 x 6407 pribeiro@calvin.edu http:/engr.calvin.edu/PRibeiro_WEBPAGE/ Modern Control Systems, 9th ed., Dorf and Bishop http:/cwx.prenhal

Lab7
School: Calvin
ENGR 315 MATLAB / SIMULINK  Laboratory # 7 Mathematical Models of Systems Objectives: To learn about PID controls. Equipment: Computer Lab PC Resources: 1  Modern Control Systems, Dorf and Bishop 2  Modern Control Systems  Analysis and Design, Bi

Flighcontrols
School: Calvin
Active Aeroelastic Wing Sarah Chandrasekar Department of Engineering, Calvin College Engineering 315 Final Paper Professor Ribeiro Abstract: Aero elastic Wing will soon take the place of today's wing control. These changes ought to generate savings i

FinalPaper_315_latest
School: Calvin
Flight Control Systems and Autopilots Brian Jewell Department of Engineering, Calvin College Engineering 315 Final Paper Professor Ribeiro Abstract: Autopilot systems have been crucial to flight control for decades and have been making flight easier,

PID1
School: Calvin
Chapter 10 The Design of Feedback Control Systems PID Compensation Networks Different Types of Feedback Control OnOff Control This is the simplest form of control. Proportional Control A proportional controller attempts to perform better than the

Harvest_Control
School: Calvin
Effects of Daylight Harvesting on Electronic Lighting Control J. S. Lester, Student Member, IEEE, and Senior Undergraduate, Calvin College AbstractAn effective control system is essential for optimizing natural day lighting and electric lighting fo

Stepservo
School: Calvin
A Detailed Study of Stepper and Servo Motor Controls Jason Flietstra, Student of Calvin College, Enrolled in Engr. 315 Control Systems AbstractAutomation and control systems have become an increasingly important aspect of industry. These systems all

DCACMotorsControl
School: Calvin
1 Overview and Control of DC and AC Motors Brian Bouma Abstract an overview of the differences in form and function between DC and AC motors. An indepth analysis of the general differential equations and transfer functions of DC and AC motors. St

315pres_diabetes
School: Calvin
Modeling GlucoseInsulin Relationship Jeremy Heersink December 6, 2002 ENGR 315 Prof. Ribeiro Outline What is diabetes? Traditional methods of treatment Model transfer function for glucoseinsulin relationship Matlab and Simulink simulations Cu

315final.pdf
School: Calvin
Heersink  1 Control Systems Representations of the Glucose Insulin Relationship and Applications for a PseudoPancreas Jeremy Heersink Abstract Control Systems can be used to model the functions of a Pancreas and the beta cells therein. Glucose and

Controlling_Wonderland
School: Calvin
ControllingWonderland A Project by Michael Bloem & Sam Schoofs The Wonderland Model Our Work: Matching Main Model Population Dream Horror Our Work: Matching Main Model Natural Capital Dream Horror Our Work: Matching Taxes Taxes = 1% Taxes = 25%

GPS_Navigation
School: Calvin
1 Kalman Filter Fundamentals and Application to Global Position Systems and Inertial Navigation Systems Paul Bakker, Student Member IEEE, Student of Calvin College III. OVERVIEW OF GPS AbstractBasic guidelines for the preparation of a technical wo

Lab7handout
School: Calvin
ENGR 315 MATLAB / SIMULINK  Laboratory # 7 Mathematical Models of Systems Objectives: To learn about PID controls. Equipment: Computer Lab PC Resources: 1  Modern Control Systems, Dorf and Bishop 2  Modern Control Systems  Analysis and Design, Bi

Syllabus
School: Calvin
Calvin College  Engineering Department Engineering 315 Control Systems Fall 2001 Professor: Textbooks: Paulo F. Ribeiro, EB133 x6407, pribeiro@calvin.edu Modern Control Systems, 9th ed., by Dorf and Bishop. Introduction Teaching / Learning Proces

Chapter3
School: Calvin
Chapter 3: State Variable Models Objectives In the preceding chapter we used the Laplace transform to obtain transfer function models representing linear, timeinvariant physical systems described by ordinary differential equations. This method is at

Finalpaper
School: Calvin
Introduction to Artificial Neural Networking Justin Jansen December 19, 2002 Abstract Neural networks have devolved from the understanding of the original biological neural network, the brain. The purpose of a neural network originally was to study

Syllabus215f2003
School: Calvin
Calvin College Engineering Department Engineering 315  Control Systems Fall 2003 Professor: Paulo F. Ribeiro SB134 x 6407 pribeiro@calvin.edu http:/engr.calvin.edu/PRibeiro_WEBPAGE/ Modern Control Systems, 9th ed., Dorf and Bishop http:/cwx.prenhal

Casebasereasoning
School: Calvin
CaseBasedReasoning MelanieHanson Engr315 WhatisCaseBasedReasoning? Storinginformationfromprevious experiences Usingpreviouslygainedknowledgeto solvecurrentproblems Similartohumanproblemsolving methods BasicSteps Identifytheproblem/case Lookfor

Chapter1
School: Calvin
Chapter 1: Introduction to Control Systems Objectives In this chapter we describe a general process for designing a control system. A control system consisting of interconnected components is designed to achieve a desired purpose. To understand the p

Summary
School: Calvin
Mark T. Gordon Engr 315 December 16, 2002 Chapter 13 Chapter 13 discusses using digital computers as controllers. Since computers are becoming cheaper and more reliable, this is becoming a more popular thing to do. It is powerful because a computer c

Neuronetvehicles
School: Calvin
Using Neural Networks to Improve the Performance of an Autonomous Vehicle By Jon Cory and Matt Edwards Our Senior Design Project Miniature autonomous vehicle that navigates an indoor maze For this project we decided to study how neural networks c

Chapter5
School: Calvin
Chapter 5 The Performance of Feedback Control Systems The ability to adjust the transient and steadystate response of a feedback control system is a beneficial outcome of the design of control systems. One of the first steps in the design process i

Chapter10PID1
School: Calvin
Chapter 10 The Design of Feedback Control Systems PID Compensation Networks Different Types of Feedback Control OnOff Control This is the simplest form of control. Proportional Control A proportional controller attempts to perform better than the