Comparison of PID and Inverter-Based Fuzzy Logic Control in an Induction Motor Blower Load
DOI:
https://doi.org/10.33387/protk.v13i3.12400Keywords:
ESP32, Inverter, Induction motor, PID controller, Fuzzy Logic Control, Blower LoadAbstract
Three-phase induction motors are among the most widely used electric motors in industrial applications due to their simple construction, low maintenance requirements, and high reliability. A common application is driving centrifugal blowers in ventilation systems and industrial processes. Controlling the speed of an induction motor under blower load is challenging because the load torque varies with the square of the rotational speed, requiring the control system to respond dynamically to load changes. This study compares the performance of two speed control methods—Proportional-Integral-Derivative (PID) and Sugeno Fuzzy Logic—implemented on a three-phase inverter-based induction motor driving a centrifugal blower using an ESP32 microcontroller. The PID method was tuned using the experimentally optimized Ziegler-Nichols method, while the Sugeno Fuzzy Logic was designed with 49 fuzzy rules based on two input variables: error and delta error. Testing was conducted at a speed setpoint of 1050 rpm, with real-time response monitored via the ESP32 Serial Monitor’s data logging. The test results showed that the PID control produced a steady-state error of 0.35%, an overshoot of 7.25%, a rise time of 19 seconds, and a settling time of 44 seconds. Meanwhile, the Sugeno Fuzzy Logic control produced a steady-state error of 0.69%, an overshoot of 27.95%, a rise time of 1.3 seconds, and a settling time of 3.9 seconds. Sugeno Fuzzy Logic outperformed the PID control in transient response speed, while the PID control was superior in steady-state accuracy and overshoot minimization.
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