scholarly journals Parameter Estimation of Permanent Magnet Synchronous Motor Using Orthogonal Projection and Recursive Least Squares Combinatorial Algorithm

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Iman Yousefi ◽  
Mahmood Ghanbari
Keyword(s):  
Parameter Estimation ◽  
Linear Regression ◽  
Least Squares ◽  
Permanent Magnet ◽  
Orthogonal Projection ◽  
Permanent Magnet Synchronous Motor ◽  
Synchronous Motor ◽  
Recursive Least Squares ◽  
Projection Algorithm ◽  
Combinatorial Algorithm

This paper presents parameter estimation of Permanent Magnet Synchronous Motor (PMSM) using a combinatorial algorithm. Nonlinear fourth-order space state model of PMSM is selected. This model is rewritten to the linear regression form without linearization. Noise is imposed to the system in order to provide a real condition, and then combinatorial Orthogonal Projection Algorithm and Recursive Least Squares (OPA&RLS) method is applied in the linear regression form to the system. Results of this method are compared to the Orthogonal Projection Algorithm (OPA) and Recursive Least Squares (RLS) methods to validate the feasibility of the proposed method. Simulation results validate the efficacy of the proposed algorithm.

scholarly journals PERMANENT SYNCHRON MAGNET MOTOR SPEED OBSERVER BASED ON LEAST SQUARES SUPPORT VECTOR MACHINE REGRESSION

2020 ◽  
Vol 13 (2) ◽  
pp. 17-24
Author(s):  
Muldi Yuhendri ◽  
Hambali Hambali ◽  
Mukhlidi Muskhir
Keyword(s):  
Support Vector Machine ◽  
Least Squares ◽  
Permanent Magnet ◽  
Permanent Magnet Synchronous Motor ◽  
Synchronous Motor ◽  
Support Vector ◽  
Motor Speed ◽  
Support Vector Machine Regression ◽  
Adaptation Mechanism ◽  
Speed Sensor

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

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