A Practical Approach for Parameter Identification with Limited Information

Lorenzo Zeni, Guangya Yang, Germán Claudio Tarnowski, Jacob Østergaard

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

A practical parameter estimation procedure for a real excitation system is reported in this paper. The core algorithm is based on genetic algorithm (GA) which estimates the parameters of a real AC brushless excitation system with limited information about the system. Practical considerations are integrated in the estimation procedure to reduce the complexity of the problem. The effectiveness of the proposed technique is demonstrated via real measurements. Besides, it is seen that GA can converge to a satisfactory solution even when starting from large initial variation ranges of the estimated parameters. The whole methodology is described and the estimation strategy is presented in this paper.
Original languageEnglish
Title of host publicationModern Advances in Applied Intelligence. Proceedings, Part II
PublisherSpringer
Publication date2014
Pages177–188
ISBN (Print)978-3-319-07466-5
ISBN (Electronic)978-3-319-07467-2
Publication statusPublished - 2014
Event27th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems - Kaohsiung, Taiwan, Province of China
Duration: 3 Jun 20146 Jun 2014
Conference number: 27

Conference

Conference27th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems
Number27
CountryTaiwan, Province of China
CityKaohsiung
Period03/06/201406/06/2014
SeriesLecture Notes in Computer Science
Volume8482
ISSN0302-9743

Keywords

  • Parameter identification
  • Genetic algorithm
  • C brushless excitation system

Fingerprint

Dive into the research topics of 'A Practical Approach for Parameter Identification with Limited Information'. Together they form a unique fingerprint.

Cite this