DC Motor Control Lab: Comparative Study of Model Predictive and PI Control Using MATLAB/Simulink

Abstract

Control engineering education requires a balance between theoretical knowledge and practical implementation, often hindered by limited laboratory resources and high costs. To address this challenge, low-cost, take-home laboratory kits have emerged as an effective alternative, enhancing hands-on learning opportunities. This study introduces the DC Motor Control Laboratory, an accessible platform designed for system modelling, parameter estimation, and control strategy testing. The work utilizes MATLAB/Simulink to implement and simulate both Model Predictive Control and classical Proportional-Integral controllers for DC motor position control. The study incorporates online resources, including MathWorks programming tools and live scripts, to support the design and testing process. A comparative analysis, exemplified through simulations and real-time experiments, demonstrates the MPC's ability to mitigate overshoot and optimize control signals, while the PI controller exhibits steady-state error and overshoot. Both simulation and real-time experimental results validate the modelling assumptions and parameter identification. This study emphasizes the importance of MATLAB/Simulink compatibility and the shared online materials in enhancing the learning experience. The findings highlight the advantages of model-based control strategies in educational settings and underscore the value of accessible, hands-on learning tools integrated with digital resources for control engineering curricula. Copyright (c) 2025 The Authors. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)