Fuzzy Logic System for Determining Accuracy and Health Level of the Servo Motor

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Nurman Setiawan, Moh Khairudin, Sigit Yatmono, Ariadie Chandra Nugraha, Muhammad Luthfi Hakim, Renaldi Anggriawan

2025 AIP Conference Proceedings Vol. 3281 Issue 1 Conference paper Cited by 0

Abstract

The accuracy and health level of the servo motor greatly influences the performance of an automation system. However, the accuracy and health level of servo motors has decreased due to excessive use. A servo motor whose accuracy decreased needs to be replaced immediately. On the other hand, the price of servo motors is relatively expensive. The aim of this research is to develop a system that can determine the accuracy and health level of a servo motor. Determination of the accuracy and health level is based on the Fuzzy Logic method. The proposed Fuzzy Logic system has two inputs there are angular error and internal temperature of the servo motor, and two output there are accuracy and health level defined in percent. Three servo motors in worn condition were used to evaluate the performance of the proposed system. The experiment result show that Servo Motor 1 has the best accuracy and health level, which are 97% and 88.24% respectively. Meanwhile, Servo Motor 3 has the lowest accuracy and health level, which are 77% and 74.65% respectively. © 2025 American Institute of Physics Inc.. All rights reserved.

Affiliations

Department of Electrical Engineering Education, Faculty of Engineering, Universitas Negeri Yogyakarta, Yogyakarta, Indonesia