Subspace identification of dynamical neurofuzzy system using LOLIMOT

Mahmood Mola*, Mojtaba Ahmadieh Khanesar, Mohammad Teshnehlab

*Corresponding author for this work

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

Abstract

In this paper a novel method for identification of dynamical neurofuzzy system is proposed. The proposed method benefits from both LOLIMOT as the premise part optimizer of the system and the subspace identification method of N4SID to optimize the state space parameters of the conclusion part. The resulting neurofuzzy system is a nonlinear dynamical system which is modeled by some locally linear state space models. using this model it is then possible to use different parallel distributed control techniques such as linear matrix inequality to control the identified system. The proposed approach is tested on a flexible robot arm and satisfactory results are generated.

Original languageEnglish
Title of host publication2010 IEEE International Conference on Systems, Man and Cybernetics, SMC 2010
Number of pages7
Publication date2010
Pages366-372
Article number5641736
ISBN (Print)9781424465880
DOIs
Publication statusPublished - 2010
Externally publishedYes
Event2010 IEEE International Conference on Systems, Man and Cybernetics, SMC 2010 - Istanbul, Turkey
Duration: 10 Oct 201013 Oct 2010

Conference

Conference2010 IEEE International Conference on Systems, Man and Cybernetics, SMC 2010
CountryTurkey
CityIstanbul
Period10/10/201013/10/2010

Keywords

  • LOLIMOT
  • N4SID
  • Neurofuzzy
  • Nonlinear identification
  • Subspace identification

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