Introduction to EGR 345

Dynamic System Modeling and Control

Goals for Today

  • you will know who I am
  • you will know what this course is all about
  • you will be excited to learn about the Laplace transform

Course Learning Outcomes

Students will

  • learn to model dynamic systems
  • learn to use the Laplace transform and transfer functions to analyze dynamic systems
  • develop a deep understanding of the dynamics of second order systems
  • use Python to model dynamic systems and analyze experimental data
  • go deeper in their knowledge of Arduinos
  • use Arduinos for dynamic systems and controls applications
  • complete a project involving dynamic systems, controls, and/or Arduinos

Four Big Ideas

By the end of the course, students will

  1. develop a deep understanding of the dynamics of second order systems
  2. be able to use Laplace to analyze the response of dynamic systems
  3. be proficient at using Python to simulate dynamic systems and analyze experimental data
  4. use Arduinos to create intelligent systems that include sensors, actuators, and possibly feedback control

Outline

  • who is Dr. Krauss?
  • what does this course cover?
    • what is a dynamic system?
      • what is a system?
      • what makes a system dynamic?
    • what do we mean by modeling?
    • what do we mean by control?
  • go over the syllabus
  • who doesn’t love differential equations?

Missy and I

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My Boys

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Joshua

Josiah

Cayden

About Me

  • born in Grand Rapids
    • grew up on the NE and NW sides
  • went to high school in Hudsonville
  • Michigan Tech - BSME (1992-1996)
  • Virginia Tech - MSEM (1996-1998)
    • nonlinear vibrations
  • taught at GVSU for one semester as an adjunct (Fall 1998)
  • safety test engineer for JCI (1999-2002)
  • Ph.D. from Georgia Tech (2002-2006)
    • modeling and control of flexible robots
  • Assistant/Associate Professor in ME at Southern Illinois Univ. Edwardsville - SIUE (2006-2016)

Course Description

From the catalog:

EGR 345 - Dynamic System Modeling and Control

An introduction to mathematical modeling of mechanical, thermal, fluid, and electrical systems. Topics include equation formulation, Laplace transform methods, transfer functions, system response and stability, Fourier methods, frequency response, feedback control, control actions, block diagrams, state variable formulation, and computer simulation. Emphasis on mechanical systems. Laboratory. (3-0-3) Offered fall semester. Prerequisites: EGR 214 and MTH 302. Admitted to interdisciplinary, mechanical, or product design and manufacturing engineering major.

Python Note

  • I am not trying to make this class about Python.
  • I am not trying to add more programming content than is typical for this class.
  • MEs (346) will learn Matlab.
  • This class used to use Scilab (open-source Matlab alternative).
  • The PDM faculty think that most of your employers will not have Matlab licenses.
  • I firmly believe that the more you know about how to take full advantage of computers, the better equipped you are for your career.
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Big Picture Questions

  • what do we mean by system?
  • what makes a system dynamic?
  • what do we mean by modeling?
    • how do we avoid doing differential equations?
  • what do we mean by control?
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Robot Demo

Goal: stop at a set distance from the wall

  • what will happen if we drive full speed and then set motor speed to zero when we get to the line?
  • what should we do instead?

Syllabus

  • go over the syllabus