Adaptive fuzzy PID controller based on online LSSVR

Kemal Ucak*, Gulay Oke

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

In this paper, a predictive adaptation method based on Online Least Square Support Vector Regression (OLSVR) for a fuzzy PID controller has been proposed. Online LSSVR model is utilized to approximate the system jacobian needed to tune controller parameters. The scaling coefficients of the controller have been tuned depending on K-step ahead future behavior of the system to provide adaptation ability to the controller under changing conditions. Controller parameters are updated using Levenberg Marquard algorithm. The purpose of this paper is to improve the control performance attained by adaptive fuzzy PID which is designed based on the Jacobian information computed by the OLSSVR. The proposed method has been evaluated by simulations carried out on a continuously stirred tank reactor (CSTR), and the results show that the control performance has been improved.

Original languageEnglish
Title of host publicationINISTA 2012 - International Symposium on INnovations in Intelligent SysTems and Applications
DOIs
Publication statusPublished - 2012
EventInternational Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2012 - Trabzon, Turkey
Duration: 2 Jul 20124 Jul 2012

Publication series

NameINISTA 2012 - International Symposium on INnovations in Intelligent SysTems and Applications

Conference

ConferenceInternational Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2012
Country/TerritoryTurkey
CityTrabzon
Period2/07/124/07/12

Keywords

  • Fuzzy PID
  • Levenberg Marquard
  • Online LSSVR

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