Effect of Filtering Techniques on the Derivative Term in Fuzzy Logic Controller for DC Motor Position Control

Year 2025, Volume: 15 Issue: 3, 872 - 888, 01.09.2025

Batın Demircan , Tuğçe Yaren

https://doi.org/10.21597/jist.1592544

Abstract

Direct Current (DC) motors are fundamental components in various industrial and automation systems, valued for their precision and controllability. Traditional control methods, such as Proportional-Integral-Derivative (PID) controllers, often require robust mathematical models and are susceptible to performance degradation under non-ideal conditions. This study investigates the implementation of Fuzzy Logic Controllers (FLC) for real-time DC motor position control, with a focus on analyzing the impact of different derivative approaches. To construct a comprehensive mathematical model of the DC motor system, both white-box and black-box system identification approaches were employed. The white-box method utilized physical principles of the motor, while the black-box method relied on empirical input-output data. The Transfer Function-Based Derivative (TFD) and Second-Order Filtered Derivative (SOFD) techniques are evaluated for their maintaining system responsiveness. A test setup utilizing an STM32F4 discovery kit was developed, and the performance of both derivative approaches was compared using a repeating stair sequence as the reference input. The experimental results showed that both techniques performed successfully, but the SOFD method demonstrated a more effective error reduction. The findings offer insights into derivative filtering techniques, highlighting the benefits of incorporating advanced filtering strategies in FLC-based control systems.

Keywords

Dc motor , Fuzzy logic control , Derivative filter , System identification , Control Theory

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