Online recursive least square parameter estimation for PMS machine

This paper presents the simulation results of the Recursive Least Squares (RLS) algorithm for estimating key motor parameters, including stator resistance and inductances. The algorithm is implemented and tested in MATLAB Simulink to evaluate its accuracy and adaptability under varying operating conditions. The results demonstrate the effectiveness of RLS in real-time parameter estimation, highlighting its potential for improving motor control precision and system stability.

Publication Details

Journal
Brno University of Technology Digital Library (Brno University of Technology)
Published
2025-01-01
Primary Topic
Fern and Epiphyte Biology
Type
article
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article

Online recursive least square parameter estimation for PMS machine

Brno University of Technology Digital Library (Brno University of Technology)
Fern and Epiphyte Biology
article

Online recursive least square parameter estimation for PMS machine

article en

Abstract

This paper presents the simulation results of the Recursive Least Squares (RLS) algorithm for estimating key motor parameters, including stator resistance and inductances. The algorithm is implemented and tested in MATLAB Simulink to evaluate its accuracy and adaptability under varying operating conditions. The results demonstrate the effectiveness of RLS in real-time parameter estimation, highlighting its potential for improving motor control precision and system stability.

Brno University of Technology Digital Library (Brno University of Technology)
Affordable and clean energy
Openalex Percentile: Top 44%
Fern and Epiphyte Biology
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Online recursive least square parameter estimation for PMS machine · Brno University of Technology Digital Library (Brno University of Technology) (2025) | TGRS Research Map | TGRS