A Universal Gains Selection Method for Speed Observers of Induction Machine - Publication - MOST Wiedzy

Search

A Universal Gains Selection Method for Speed Observers of Induction Machine

Abstract

Properties of state observers depend on proper gains selection. Each method of state estimation may require the implementation of specific techniques of finding those gains. The aim of this study is to propose a universal method of automatic gains selection and perform its verification on an induction machine speed observer. The method utilizes a genetic algorithm with fitness function which is directly based on the impulse response of the observer. System identification using least-squares estimation is implemented to determine the dynamic properties of the observer based on the estimation error signal. The influence of sampling time as well as signal length on the system identification has been studied. The results of gains selection using the proposed method have been compared with results obtained using the approach based on the placement of the poles of linearized estimation error equations. The introduced method delivers results comparable with analytical methods and does not require prior preparation specific to the implemented speed observer, such as linearization.

Citations

  • 0

    CrossRef

  • 0

    Web of Science

  • 0

    Scopus

Cite as

Full text

download paper
downloaded 1 times
Publication version
Accepted or Published Version
DOI:
Digital Object Identifier (open in new tab) 10.3390/en14206790
License
Creative Commons: CC-BY open in new tab

Keywords

Details

Category:
Articles
Type:
artykuły w czasopismach
Published in:
ENERGIES no. 14,
ISSN: 1996-1073
Language:
English
Publication year:
2021
Bibliographic description:
Wachowiak D.: A Universal Gains Selection Method for Speed Observers of Induction Machine// ENERGIES -Vol. 14,iss. 20 (2021), s.6790-
DOI:
Digital Object Identifier (open in new tab) 10.3390/en14206790
Verified by:
Gdańsk University of Technology

seen 6 times

Recommended for you

Meta Tags