CBE 32338 Process Control Laboratory
This repository comprises a collection of Jupyter/Python notebooks supporting the hands on learning of process control in the laboratory sessions associated with CBE 30338 Chemical Process Control taught at the University of Notre Dame.
The links below display the notebooks as HTML web pages. You can download these notebooks to run on your own laptop. To run on your own laptop you will need to install Jupyter and Python 3, such as the Anaconda distribution from Continuum Analytics.
Please let me know (jeff at nd.edu) if you any thoughts or suggestions on how these notebooks could be improved for teaching and learning the principles of Chemical Process Control.
Table of Contents
Chapter 1.0 Introduction to the Temperature Control Laboratory
- 1.1 The Temperature Control Laboratory
- 1.2 The TCLab Python Package
- 1.11 TCLab Lab 1: Coding a relay controller
Chapter 2.0 Model Identification
- 2.1 Step Testing
- 2.2 Fitting Step Test Data to Empirical Models
- 2.3 First Order Model for a Single Heater
- 2.4 Two-Input, Two-Output Model
- 2.5 Two State Model for a Single Heater
- 2.6 Four State Model
- 2.10 TCLab Lab 2: Model Identification
- 2.10 TCLab Lab 2: Model Identification
- 2.11 Model Identification: Fitting models to data
Chapter 3.0 State Estimation
Chapter 4.0 Feedback Control
- 4.1 Relay Control
- 4.3 PID Control
- 4.10 Lab Assignment: PID Control
- 4.11 Lab Assignment 4: PI Control
Chapter 5.0 Predictive Control and Real Time Optimization
- 5.1 Simulation, Control, and Estimation using Pyomo
- 5.2 Simulation, Control, and Estimation using Pyomo
Appendix A. Additional Python
- A.1 Coding Controllers with Python Generators
- A.2 Modular Simulation using Python Generators
- A.3 A Modular Approach to Simulation using Python Generators
- A.4 Animation in Jupyter Notebooks
License Requirements. The materials in this repository are available at https://github.com/jckantor/CBE2338.git for noncommercial use under terms of the Creative Commons Attribution Noncommericial ShareAlike License. You are invited to fork this repository, and to use, adapt, remix these material for non-commericial purposes. The license terms require you to give attribution and share your work under the same terms.