Permanent Synchron Magnet Motor Speed Observer Based on Least Squares Support Vector Machine Regression - Muldi Yuhendri; Hambali Hambali; Mukhlidi Muskhir (Universitas Negeri Padang, 2020)
Motor speed control requires motor speed data as feedback from control actions. Motor speed data is usually obtained from the speed sensor. In this paper, the motor speed observer for permanent magnet synchronous motor is proposed to obtain motor speed data based on motor back emf voltage making it more economical without a speed sensor. The Speed observer is designed based on the Model Reference Adapative System (MRAS) with using Least Squares Support Vector Machine Regression (LSSVMR) algorithm for adaptation mechanism tools. The proposed speed observer is tested with varying motor speeds. The test results show that the MRAS-based motor speed observer using LSSVMR has successfully estimated the rotation speed of the permanent magnet synchronous motor based on the back emf motor voltage. It can be seen from the maximum error of the motor speed, ie only 3.7 rpm at transient conditions and close to zero at steady state