Speed control of sensorless PMSM drive based on EKF optimized by variable scale chaotic particle swarm optimization

To investigate the parameter characteristics of permanent magnet synchronous motor (PMSM) speed sensorless vector control system and capture the noise matrices quickly and accurately in the speed estimation process of the extended Kalman filter for PMSM, The recursive least square method with forget...

Full description

Saved in:
Bibliographic Details
Published in:Measurement and control (London) 2024-07, Vol.57 (7), p.981-991
Main Authors: Zhao, Qiang, Zhao, Zihan, Yang, Zhao, Liu, Wei
Format: Article
Language:English
Subjects:
Algorithms
Chaos theory
Control systems
Directional control
Extended Kalman filter
Noise control
Noise measurement
Parameter estimation
Particle swarm optimization
Permanent magnets
Recursive functions
Speed control
Synchronous motors
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:To investigate the parameter characteristics of permanent magnet synchronous motor (PMSM) speed sensorless vector control system and capture the noise matrices quickly and accurately in the speed estimation process of the extended Kalman filter for PMSM, The recursive least square method with forgetting factor is proposed to determine the actual parameters of the system, and then a new variable-scale chaotic particle swarm optimization (VCPSO) algorithm is put forward to accurately obtain the system noise matrix and the measurement noise matrix. The simulation results show that noise matrix optimization of extended Kalman filter by employing VCPSO algorithm under actual motor parameters is better than those employing standard PSO or chaotic PSO algorithms with faster speed and higher accuracy.
ISSN:0020-2940
2051-8730
DOI:10.1177/00202940231224220