A modular, portable lab for learning Process Control
The BYU Arduino Temperature Control Lab is designed as a modular, portable, and inexpensive solution for hands-on process control learning. Heat output is adjusted by modulating the voltage to a transistor. A thermistor measures the temperature. Energy from the transistor output is transferred by conduction and convection to the temperature sensor. The lab is integrated into a small PCB shield which can be mounted to any Arduino or Arduino compatible microcontroller. Experiments can then be programmatically controlled using Python over a USB connection.
This lab reinforces principles of system dynamics, estimation, and model predictive control, including:
- The difference between manual and automatic control
- Step tests to generate dynamic data for empirical modeling
- Dynamic modeling with first principles
- Dynamic data reconciliation
- Tune a moving horizon estimator
- Tune a PID controller
- Tune a model predictive controller
- Combine MHE and MPC
For instructions on configuring your system and getting started with the lab see Getting Started.
The following example modules are included
Perform a step test to collect dynamic data. Steps the input voltage up and down and records output temperatures.
Demonstrates the use of regression in Python to fit first order, second order, and ARX models to collected data.
Demonstrates control to a desired setpoint using a binary On/Off controller.
Demonstrates control to a desired setpoint using a Proportional, Integral, Derivative controller.
Shows how model parameters can be dynamically estimated during system operation using MHE.
Demonstrates advanced control to a desired setpoint using a Model Predictive Controller.
Combines MHE for online model parameter estimation with advanced MPC control to reach a desired setpoint.
For more information and instructional videos, visit the Arduino temperature control lab page on the BYU Process Dynamics and Control course website.
A Matlab version of the lab is also available.