Arduino Temperature Control Lab for Simulink and MATLAB
This plug-and-play lab reinforces transient modeling, parameter estimation, and feedback control to maintain temperature. 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 the purpose of reinforcing control theory for students. Many universities around the world have adopted this lab for process control education. The lab is also used for the online courses Process Dynamics and Control (https://apmonitor.com/pdc) and Dynamic Optimization (https://apmonitor.com/do).
This lab teaches principles of system dynamics and control. In particular, this lab reinforces:
Dynamic modeling with balance equations
The difference between manual and automatic control
Step tests to generate dynamic data
Fitting dynamic data to a First Order Plus Dead Time (FOPDT) model
Obtaining parameters for PID control from standard tuning rules
Tuning the PID controller to improve performance Process Control Temperature Lab
Instructions are available for building the kit at http://apmonitor.com/che436/uploads/Main/Hands_on_Process_Control_CACHE.pdf or for purchase from https://apmonitor.com/heat.htm
Citar como
John Hedengren (2024). Arduino Temperature Control Lab for Simulink and MATLAB (https://www.mathworks.com/matlabcentral/fileexchange/65760-arduino-temperature-control-lab-for-simulink-and-matlab), MATLAB Central File Exchange. Recuperado .
Compatibilidad con la versión de MATLAB
Compatibilidad con las plataformas
Windows macOS LinuxCategorías
- Control Systems > Control System Toolbox > Control System Design and Tuning > PID Controller Tuning >
Etiquetas
Agradecimientos
Inspirado por: Real-Time Pacer for Simulink
Inspiración para: Single-Heater-Response, First-Order-Plus-Dead-Time-Models, Semi-Empirical-Model-Estimation-Regression
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