A Novel Online Multivariate Identification for Autotuning Speed Control in PMSM Drives

Joint Authors

Chen, Ke
Ai, Wu
Chen, Bing
Liu, Yi

Source

Mathematical Problems in Engineering

Issue

Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-13, 13 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2016-02-29

Country of Publication

Egypt

No. of Pages

13

Main Subjects

Civil Engineering

Abstract EN

A novel online algorithm to identify the moment of inertia, viscous friction coefficient, and load torque of PMSM (Permanent Magnet Synchronous Motor) drives and a distinctive autotuning speed control scheme are presented.

The proposed identification algorithm does not require motors run in a particular trajectory and only needs a short identification time.

A Luenberger speed observer is introduced to eliminate noises which are generated by the detection of position signal and to improve the accuracy of identified parameters.

Parameters of the speed controller are optimized by analyzing the mathematical model of the system and the formula of the PI controller.

Compared to a standard recursive least squares method (RLSM) and traditional PI algorithm, the effectiveness of the proposed identification algorithm and autotuning speed control scheme are validated through simulations and experiments.

American Psychological Association (APA)

Chen, Ke& Ai, Wu& Chen, Bing& Liu, Yi. 2016. A Novel Online Multivariate Identification for Autotuning Speed Control in PMSM Drives. Mathematical Problems in Engineering،Vol. 2016, no. 2016, pp.1-13.
https://search.emarefa.net/detail/BIM-1111793

Modern Language Association (MLA)

Chen, Ke…[et al.]. A Novel Online Multivariate Identification for Autotuning Speed Control in PMSM Drives. Mathematical Problems in Engineering No. 2016 (2016), pp.1-13.
https://search.emarefa.net/detail/BIM-1111793

American Medical Association (AMA)

Chen, Ke& Ai, Wu& Chen, Bing& Liu, Yi. A Novel Online Multivariate Identification for Autotuning Speed Control in PMSM Drives. Mathematical Problems in Engineering. 2016. Vol. 2016, no. 2016, pp.1-13.
https://search.emarefa.net/detail/BIM-1111793

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1111793