This is a collection of class materials for CBE 303338 Data Analytics, Optimization, and Control taught at the University of Notre Dame.
Dynamic modeling, data analytics, optimization, and control are essential to modern chemical technologies that enable precision medicine, sustainable energy, semiconductors, access to clean water, and beyond. In CBE 30338, students combine their knowledge of chemical engineering fundamentals (e.g., thermodynamics, transport, kinetics) and data analytics to develop dynamic models of diverse chemical technologies and processes. These models enable the design and optimization of control systems that use feedback to reject disturbances and drive systems to steady-state setpoints. CBE 30338 combines state-space modeling with modern computational and statistical methods to cover industrially relevant topics such as model predictive control, parameter estimation, and optimization. Students master techniques in hands-on experiments and a final semester project.
Weeks | Unit |
---|---|
1 | Introductions to the Course and TC Lab |
1 - 4 | Dynamic Modeling and Data Analytics |
5 - 7 | Feedback Control |
7 - 9 | Computational Optimization |
10 - 11 | Predictive Control |
12 - 13 | Team Project Workshops |
14 | Student Project Presentations |
Install Software (personal computer):
miktex
to the end of the above commandOpenning Anaconda:
Students In the terminal/prompt, type:
conda create -n controls -c anaconda -c conda-forge -c IDAES-PSE python=3.10 pandas numpy matplotlib scipy jupyterlab nb_conda_kernels pandoc nbconvert-pandoc idaes-pse
Instructor/TAs In the terminal/prompt, type:
conda create -n controls -c anaconda -c conda-forge -c IDAES-PSE python=3.10 pandas numpy matplotlib scipy jupyterlab nb_conda_kernels pandoc nbconvert-pandoc jupyter-book ghp-import
Everyone Next, in the terminal type:
conda activate controls
(activates the new environment)idaes get-extensions
(installs optimization solvers)pip install tclab
(installs TCLab software)To start using Python, in either the Acaconda prompty (Windows) or terminal (Mac):
conda activate controls
jupyter lab
Students will use their personal laptop computers to complete labratory and homework assignments. Below are instructions
Start Here:
conda create -n controls python=3.10
conda activate controls
Extra Steps for Website Contributors (e.g., instructor, TAs, students please skip):
conda install -c conda-forge jupyter-book
conda install -c conda-forge ghp-import
Everyone (students resume here after "Start Here" steps are complete):
conda install -c conda-forge jupyterlab
conda install nb_conda_kernels
conda install -c anaconda pandas numpy matplotlib scipy
conda install -c IDAES-PSE -c conda-forge idaes-pse
idaes get-extensions
pip install tclab
To run Python, in either the Acaconda prompty (Windows) or terminal (Mac):
conda activate controls
jupyter lab
Most of these materials were developed by Prof. Jeffery Kantor. The repository is currently maintained by Prof. Alexander Dowling at https://github.com/ndcbe/controls.