CHE 466 - Process Dynamics and Controls

Overview
Materials

CSTR Heat Exchange Model Group for ChE 466, Fall 2006, under a Creative Commons License: BY.

Term:

Fall 2008

Published:

March 12, 2009

Revised:

June 5, 2015

MERLOT: Multimedia Educational Resource for Learning and Online Teaching

This course uses an open textbook University of Michigan Chemical Engineering Process Dynamics and Controls. The articles in the open textbook (wikibook) are all written by teams of 3-4 senior chemical engineering students, and are peer-reviewed by other members of the class. Using this approach, the faculty and Graduate Student Instructors (GSIs) teaching the course act as managing editors, selecting broad threads for the text and suggesting references. In contrast to other courses, the students take an active role in their education by selecting which material in their assigned section is most useful and decide on the presentation approach. Furthermore, students create example problems that they present in poster sessions during class to help the other students master the material.

This project is a collaboration between the faculty and students of the University of Michigan chemical engineering department. The goal of this project is to provide the greater chemical engineering community with a useful, relevant, high quality, and free resource describing chemical process control and modeling. Initial construction of this resource began in Fall 2006, and will continue in future years with other groups of students.

Please refer to the course wikibook for additional Chem 466 materials, including video files, which are not included here.

Instructor: Peter Woolf

Course Level: Undergraduate

Course Structure: Two hour lecture, twice a week

Available on: iTunes U and YouTube

This book is available as volume I and volume II through University of Michigan Library's Print-On-Demand Service with Espresso Book Machine. This service is only available for individuals within the Ann Arbor area.

Syllabus

Course Description

As a practicing chemical engineer, you will be faced with the task of doing things reliably in an uncertain world and with imperfect understanding. In this course we will show you a variety of approaches to reduce or manage this uncertainty through the use of robust designs, dynamic systems theory, nonlinear dynamics, control theory, and statistics.

The structure of the course this year has been changed significantly to accommodate a more flexible and interactive learning environment. The primary difference in this course is that lectures have been (and are being) pre-recorded so that they can be viewed at any time via the web or pod cast. Recording lectures provides you with two advantages: (1) flexibility and (2) better use of time. With a recorded lecture, you can watch the lectures whenever you like, wherever you like, at any speed you like, and as many times as you like. With lecture time moved to outside of the course, we can allocate the time we have in the scheduled class meeting time for interactive work and smaller group question and answer sessions.

A second difference of this course is in wiki form, and as such is something that we all are actively responsible for creating and maintaining. This text is freely available online athttp://controls.engin.umich.edu/wiki.

Web Site

This course has two websites. The first is a University of Michigan CTools website (http://ctools.umich.edu) If you have already signed up for the course, then the appropriate courses should already be selected for you. Otherwise, search for “process control” to find the course. On this site we will post additional reading material and much of the paperwork of the course.

The second website is the wiki textbook site. To edit this site, you will need to sign up for an account to the site. This restricted account will allow only members of the class to edit and upload content on the site.

Wiki Edits

Part of your grade will depend on improving the content on the wiki. Click here (http://controls.engin.umich.edu/wiki/index.php/edits) for criteria for receiving credit and examples of wiki edits that received credit.

Learning Objectives

Objectives

At the conclusion of this course you should be able to:

Describe a process, how it works, and what your control objectives are
Instrument a process
Describe processes with appropriate diagrams
Numerically model a process from physical and logical models
Fit a model to data
Understand feed-forward, feed-back, and PID control of systems
Tune process controllers
Understand the principles behind multi-objective control architectures
Predict product quality range for a process
Identify sensitivities in process models

Reading List

Textbook & Reading Assignments

There is no textbook purchase required for this course—the text is the wiki. The course projects, exams, quizzes, and homework will all be derived from this source. In addition, lectures will be linked from the text for viewing online or download. Students are responsible for all material in the wiki readings and lectures.

Note that this class has a lot of reading, and you will not be able to digest all of the material in detail. Your job in this class is to keep up with the readings and to learn the concepts behind the topic.

Other Texts that may also be of Interest

ECOSSE HyperCourse (http://eweb.chemeng.ed.ac.uk/courses/control/restricted/course/index.html) on control theory from the university of Edinburgh, Scotland.
David MacKay's text (http://www.inference.phy.cam.ac.uk/mackay/itila/book.html) on Information Theory, Inference, and Learning Algorithms. This text provides a solid foundation for probability theory.
Video lectures on linear algebra (http://ocw.mit.edu/OcwWeb/Mathematics/18-06Spring-2005/VideoLectures/index.htm) from MIT's open courseware. If you want to learn more about eigenvalues, eigenvectors, determinants, and SVD, here is a good place to go!

About the Creators

Dr. Peter J. Woolf

Peter Woolf is an Assistant Professor College of Engineering Department of Chemical Engineering. The goal of the research in my group is to integrate experimental data together to create computational, systems-level models of how cancer initiates and grows.

B.S. Cornell University, Chemical Engineering
Ph.D. University of Michigan, Chemical Engineering