Experimental data from an open-source DC motor control educational kit for calibration, system identification, and controller validation.

This data article presents raw and processed experimental data collected with the OpenMCT DC motor control educational kit. The dataset includes current-sense calibration data, static motor characterization data, system-identification logs at four sampling times, continuous PI controller validation at four loop periods, discrete controller validation for three controller designs, and an additional chirp-excitation characterization run. The raw acquisition files were exported from the OpenMCT Python/Qt graphical user interface as comma-separated text files containing reference commands, measured speed, loop interval, raw and filtered current-sense values, PWM command, and synchronized digital multimeter measurements. MATLAB scripts, processed files, model tables, screenshots, and exported figures are provided to reproduce the data organization and plots. The records can be used to prepare laboratory exercises in which students identify a motor model and compare its predicted response with experimental measurements. They also provide reference data for evaluating alternative identification and controller-validation methods.