Parameter identification and continuous friction modelling of a brushed DC motor

Abstract

Designing high-performance control systems for brushed DC motors is often hindered by the lack of comprehensive dynamic parameters in manufacturer datasheets, particularly for low-cost DC motors. In addition to the parameter identification method, this study also introduces a continuously differentiable friction model incorporating Coulomb and viscous-like behaviors using a hyperbolic tangent function. The electrical and mechanical parameters of an RS-775 motor were identified using standard laboratory tools and the MATLAB system identification toolbox. The proposed model was validated against experimental data under square wave and sinusoidal inputs, achieving a position prediction error of less than 5% and capturing complex dynamic behaviors. The results demonstrate that this accessible identification approach provides a sufficiently accurate dynamic model for educational and industrial robotics applications, offering a superior alternative to trial-and-error tuning.