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Process Dynamics and Control in MATLAB

This course focuses on a complete start to finish process of physics-based modeling, data driven methods, and controller design. Although some knowledge of computer programming is required, students are led through several introductory topics that develop an understanding of numerical methods in process control. Students should start with the Begin MATLAB Short Course that takes 2-3 hours to complete.

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This course focuses on methods that are used in practice for simple or complex systems. It is divided into three main parts including (1) data driven modeling and controller development, (2) physics-based modeling and controller development, and (3) advanced controls with optimization. Example problems are provided throughout in the MATLAB programming language.

Professor

John Hedengren leads the BYU PRISM group with interests in combining data science, optimization, and automation with current projects in hybrid nuclear energy system design and unmanned aerial vehicle photogrammetry. He earned a doctoral degree at the University of Texas at Austin and worked 5 years with ExxonMobil Chemical prior to joining BYU in 2011.

Teaching Assistant

Joshua Hammond is an experienced researcher in Process Systems Engineering leveraging Data Science, Machine Learning, Optimization, and domain knowledge to achieve optimal solutions. Joshua developed the MATLAB dynamics and control course from the Python version with technical support from Colin Anderson and Nathanael Nelson. Assignment solution videos are published to the Horizon PSE YouTube Channel.

Course Objectives

It is the intent of this course to help the student to:

1. Understand and be able to describe quantitatively the dynamic behavior of process systems.
2. Learn the fundamental principles of classical control theory, including different types of controllers and control strategies.
3. Develop the ability to describe quantitatively the behavior of simple control systems and to design control systems.
4. Develop the ability to use computer software to help describe and design control systems.
5. Learn how to tune a control loop and to apply this knowledge in the laboratory.
6. Gain a brief exposure to advanced control strategies.

Course Schedule

MATLAB and Python Repository on Github

Course Web-site and Schedule

View the Repository on MATLAB Drive

Temperature Control Lab

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The materials in this archive are released under the MIT License. The financial assistance of MathWorks is gratefully acknowledged with technical assistance of Melda Ulusoy and others at MathWorks.