Ready to develop the control skills valued in today’s process industry?
This online course is a hands-on approach to learning process control and systems dynamics—skills in high demand in the process industry according to an NSF-sponsored report. Industrial control expert John Hedengren will lead you through a complete start-to-finish process of physics-based modeling, data-driven methods and controller design.
If you have some knowledge of computer programming, take this course. You’ll walk through several introductory topics that develop your understanding of numerical methods in process control while you build skills you can apply to solve real problems in your operating plant.
Turn process control theory into practice
Throughout this course, you’ll gain hands-on experience that will improve your performance as a control engineer, instrument engineer or process engineer or as a developer of digital twins or automation strategies for new processes. You’ll increase your confidence through unique access to interactive simulations and control challenge problems. You’ll take your proficiency to the next level using computer-aided tools, video solutions, step-by-step instructions, and hardware exercises. In addition, your understanding of simulation and theory will be reinforced as you develop a dynamic model and controller with real data using an Arduino-based Temperature Control Lab.
You have the mathematical skills from dynamics and control required to solve idealized textbook problems. Take the next step in this online course where you’ll gain new knowledge and be equipped to apply it to control challenges in today’s demanding process industry.
If you have some experience with Python already, you may consider taking ELA270: Introduction to Python for Chemical Engineers and ELA271: Introduction to Data Science with Python
Learning Outcomes:
- Describe quantitatively the dynamic behavior of process systems
- Describe the fundamental principles of classical control theory, including different types of controllers and control strategies.
- Describe quantitatively the behavior of simple control systems and to design control systems
- Use computer software to help describe and design control systems
- Tune a control loop and apply this knowledge in the laboratory
- Control engineers, instrument engineers, process engineers, digital twin developers, data scientists
- Professionals in chemicals, oil & gas, medical, manufacturing, food & beverage, mining & materials, energy and data industries
- Professionals with responsibilities in automation, simulation, control and instrumentation
- Understand and be able to describe quantitatively the dynamic behavior of process systems.
- Learn the fundamental principles of classical control theory, including different types of controllers and control strategies.
- Develop the ability to describe quantitatively the behavior of simple control systems and to design control systems.
- Develop the ability to use computer software to help describe and design control systems.
- Learn how to tune a control loop and to apply this knowledge in the laboratory.
- Gain a brief exposure to advanced control strategies.
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