Speed control of induction motor using fuzzy logic based on internet of things

The aim of this research was to propose an innovative method of controlling the speed of an induction motor (IM) using fuzzy logic, integrated with internet of things (IoT). To achieve this aim, fuzzy logic was used to increase the performance of IM in order to obtain stable speed and high system response even in the presence of disturbances. Moreover, fuzzy logic relied on rules that used linguistic variables, and its main advantage was simple yet highly accurate, enabling the system to be efficient for determining parameters compared to the time-consuming and inefficient trial-and-error method. In this research, IoT implementation used Blynk platform to control and monitor IM speed remotely. Additionally, the components used in this research included an inverter, gate driver, Arduino Mega 2560, and NodeMCU ESP8266. Pulse width modulation (PWM) was required to obtain rotational speed of the motor through MOSFET switching process. The gate driver amplified PWM signal from Arduino Mega 2560, allowing MOSFET to operate. As a result, IM achieved a stable speed, and the system response followed the reference using fuzzy logic. In addition to this process, the system could be controlled and monitored remotely. Finally, the control system was successful, and the results were presented to show the viability of the proposed method.