Comparative Analysis of Fuzzy Logic and PID Controller for Speed Control
Keywords:
Fuzzy logic controller, Overshoot, PID controller, Rise time, Settling time, Speed controlAbstract
Controlling the speed of electric drives is very important in current industrial, automation, and intelligent control systems. A lot of people employ regular Proportional Integral Derivative (PID) controllers because they are easy to understand; however, they do not work as well when the system is nonlinear, the parameters change, or the operating conditions are unclear. Fuzzy Logic Controllers (FLCs) have recently become a good choice since they can control things without using models or rules. This study provides a comparative examination of PID and fuzzy logic controllers for motor speed regulation under identical simulation settings in MATLAB/Simulink. We use rising time, settling time, and % overshoot as the main dynamic performance indicators to compare how well both controller’s work. The simulation findings show that the fuzzy logic controller has a faster rise time (0.32 s), a shorter settling time (0.85 s), and a much smaller overshoot (3.8%) than the PID controller, which has a bigger overshoot (12.5%) and a slower dynamic response. These results confirm the superior robustness and adaptability of fuzzy logic control under uncertain conditions. The significance of this study lies in its applicability to near-future intelligent systems, such as electric vehicles, robotics, smart manufacturing, and adaptive drive systems, where robustness and real-time performance are essential. The findings highlight fuzzy logic control as a promising solution for next-generation intelligent and autonomous control applications.
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