Temperature Control Lab

This lab is an application of feedback control for a temperature control device. There are two heaters and two temperature sensors. The heater power output is adjusted to maintain a desired temperature setpoint. Thermal energy from the heater is transferred by conduction, convection, and radiation to the temperature sensor. Heat is also transferred away from the device to the surroundings. This lab is a resource for model identification and controller development. It is a pocket-sized lab with software in Python, MATLAB, and Simulink for the purpose of reinforcing control theory for students.

Portable Temperature Control Lab for Learning Process Control

This lab teaches principles of system dynamics and control. In particular, this lab reinforces:

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Student Resources (MATLAB/Simulink and Python)

Instructor and Development Resources

Lab Instructions

Steps 1-3 with the single heater should be completed with this lab. The dual heater models and advanced control modules are included as additional but optional information.

A report is due at the end of the project that details the modeling, parameter estimation, and control performance.

Students are assembled into groups of two for this lab. One report should be submitted for each group.

Advanced Control Methods

The temperature control lab is also used for Advanced Estimation and Control in the Dynamic Optimization Course. The difference between the PID lab and the advanced control methods is that the model is directly used to control the process versus only for tuning correlations. This approach is called Model Predictive Control (MPC) because the simulated system is driven to a desired set point with the use of an optimizer. Also, instead of estimating the model once from step tests, Moving Horizon Estimation (MHE) updates the model with every new measurement. The updated model is transferred to MPC for improved performance through adaptive control.

The 2015 NSF-sponsored report Chemical Engineering Academia-Industry Alignment: Expectations about New Graduates identifies a strong industrial need for practical understanding of process control and system dynamics. Industry feedback also suggests more weight on translating process control theory to practice. To meet this need, laboratory experiences are integrated into many process control courses. With the growth of enrollment in chemical engineering, laboratory resources are often strained and scheduling for these labs can be difficult to manage. For this reason, we developed a pocket-sized process control lab that reinforces process control theory and is available to groups of two students each.

We give the small and inexpensive process control experiment to students to reinforce concepts in dynamics and control theory. A few other universities are currently adopting this lab for process control instruction. Current participating universities include Notre Dame, Iowa State, Oklahoma State, Georgia Tech, New York University, Louisiana Tech, McMaster University, Christian Brothers University, Villanova, University of Iowa, Brigham Young University, University of Pretoria, Western Michigan University, and others. This lab was presented at the 2017 ASEE Summer School at NCSU as part of resources for teaching process transient analysis. Lab solutions for instructors are provided in Python and MATLAB. Instructors can join a bulk order by filling out an information form. The lab is also available for purchase from the PayPal link below. The lab kit includes:

  • Arduino Uno or Arduino Leonardo
  • Temperature control PCB shield
  • USB barrel jack power cable for heaters
  • 5V USB power supply (US plug, EU/UK plugs available on request)
  • USB cable for serial connection to MacOS, Windows, or Linux computer
  • Small cardboard box
Lab Type
Arduino Firmware (can change later)
Other notes (e.g. EU Plug)

Over 900 lab kits have been distributed to destinations around the world to individuals and universities. Software is available in Python, Simulink, and MATLAB with basic or advanced modules.