<![CDATA[DC motors are common in industry due to their simplicity, reliability, and ease of control. However, their speed regulation is sensitive to parameter changes and load disturbances. Variations in parameters like damping coefficients, caused by friction, temperature, and wear, can impair fixed-gain PID controllers. This paper introduces an adaptive fuzzy-PID auto-tuning (AFPAT) scheme to ensure robust speed control amid uncertainties and load disturbances. The controller uses a Sugeno fuzzy system to adjust PID gains online based on speed error (e) and derivative error (de). A second-order DC motor model assesses robustness by varying damping coefficients across five scenarios (4.54 ≤ a1 ≤ 13.62) and a 50 rpm load disturbance at 900 rpm setpoint. Performance measures include steady-state error, overshoot, settling time, and recovery time post-disturbance. Results show the controller achieves zero steady-state error and overshoot with settling times from 2.74 to 4.28 seconds and recovery times from 3.05 to 4.58 seconds. Compared to open-loop, with a steady-state error of 2963, the controller demonstrates robust speed regulation under parameter variations and disturbances.]]>
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