Implementasi Adaptive Neuro Fuzzy Inference System (ANFIS) untuk Estimasi Kecepatan Motor Induksi - Dicky Rivaldo Ramdani; Novie Ayub Windarko; Era Purwanto (Universitas Nahdlatul Ulama Blitar, 2025)
Three-phase induction motors are a major component in industrial machinery due to their simple construction, robustness, relatively low cost, easy maintenance, and high reliability. However, these motors have disadvantages in speed regulation due to their non-linear characteristics, which cause difficulties in maintaining a constant speed when the load changes. This research aims to maintain the speed of induction motors to remain constant by using the Adaptive Neuro-Fuzzy Inference System (ANFIS) method. This ANFIS method goes through the stages of data collection, data processing, ANFIS system design, ANFIS training, validation testing, and finally analyzing the results. The input of the induction motor speed estimation system is through a mathematical equation model in d-q coordinates. The output of this system is speed. In this study, training and testing variations. The smallest RMSE result obtained is with the Trapzeium membership function architecture with the number of epochs 100 of 0.0187542.