Process Dynamics and Control Course

Matlab Dynamics and Control course with Live Scripts and the Temperature Control Lab

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 Process Dynamics and Control Course 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

Class	Topic	Assignment	TCLab Activity
L01	Course Introduction	Begin MATLAB	Begin MATLAB (Continued)
L02	Simulate Dynamics in MATLAB	Simulate HIV Infection	Step Test Simulation
L03	Physics-based Dynamic Modeling	Derive Balance Equations	Convective Heat Transfer
L04	Transient Balance Equations	Tank Blending Simulation	Radiative Heat Transfer
L05	Linearize Balance Equations	Linearize Differential Equations	Linearize Energy Balance
L06	First-Order Linear Dynamics with Dead Time using Graphical Fitting Methods	Graphical FOPDT Fit	TCLab Graphical FOPDT Fit
L07	Optimize Model Parameter Fit	Parameter Regression	Regression FOPDT
L08	Exam Review on Modeling and Dynamics	Practice Exam
L09	Exam on Dynamic Modeling
Class	Topic	Assignment	TCLab Activity
L10	Control Design	Controller Design Exercise	TCLab Controller Design
L11	Proportional-only (P-only) Control	Tank Level	P-only Control
L12	Proportional Integral (PI) Control	Auto Cruise Control	PI Control
L13	Proportional Integral Derivative (PID) Control	Blending Control	PID Control
L14	Case Study: Level Control	Level Control	PI Control Tuning
L15	Case Study: Nonlinear System Control	Exothermic Reactor	PID Control Tuning
L16	Case Study: Disturbances	Type-I Diabetic Blood Glucose	PID with Feedforward
L17	Valve Design Principles	Valve Design Exercise	Heater Actuator
L18	Sensors and Data Acquisition	Sensor Design Exercise	Temperature Sensor
L19	Exam Review on Sensors, Actuators, and Controllers	Practice Exam
L20	Exam on Sensors, Actuators, and Controllers
Class	Topic	Assignment	TCLab Activity
L21	Single Heater Modeling	TCLab Project Overview	Dual Heater Modeling 2
L22	Single Heater Regression		Dual Heater Regression 2
L23	Single Heater Control	2 Page Report	Dual Heater Control 2
L24	Laplace Transforms	Laplace Transform Applications	Impulse Response
L25	Transfer Functions	Block Diagrams with Transfer Functions	Block Diagram
L26	State Space Models	Reactor State Space	State Space Simulation
L27	Second Order Systems with Graphical Fitting	Second Order Estimation: Graphical	On/Off Control
L28	Second Order Optimization	Second Order Estimation: Optimization	Second Order Regression
L29	Simulation of FOPDT, SOPDT, and Higher Order Systems	Distillation Control	Higher Order Regression
L30	Stability Analysis	Controller Stability Limits	P-Only Stability Analysis
L31	Cascade Control and Feedforward Control	Cascade or Feedforward Control Design	Cascade Control
L32	Exam Review on Dynamic Systems Analysis	Practice Exam
L33	Exam on Dynamic Systems Analysis
Class	Topic	Assignment	TCLab Activity
L34	Control Project Introduction	Control Project
L35	Optimization Introduction	Control Project
L36	Linear Programming	Control Project
L37	Scheduling Optimization	Control Project
L38	Nonlinear Programming	Control Project
L39	Machine Learning Classification	Control Project
L40	Model Predictive Control	Control Project
L41	Project Help Session	Control Project
L42	Final Exam Review	Practice Exam
Final	Project Report (2 pages) and Presentation (5 min) Final Exam

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.