An improved adaptive PID controller based on online LSSVR with multi RBF kernel tuning

Kemal Ucak*, Gulay Oke

*Corresponding author for this work

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

10 Citations (Scopus)

Abstract

In this paper, the effects of using multi RBF kernel for an online LSSVR on modeling and control performance are investigated. The Jacobian information of the system is estimated via online LSSVR model. Kernel parameter determines how the measured input is mapped to the feature space and a better plant model can be achieved by discarding redundant features. Therefore, introducing flexibility in kernel function helps to determine the optimal kernel. In order to interfuse more flexibility to the kernel, linear combinations of RBF kernels have been utilized. The purpose of this paper is to improve the modeling performance of the LSSVR and also control performance obtained by adaptive PID by tuning bandwidths of the RBF kernels. The proposed method has been evaluated by simulations carried out on a continuously stirred tank reactor (CSTR), and the results show that there is an improvement both in modeling and control performances.

Original languageEnglish
Title of host publicationAdaptive and Intelligent Systems - Second International Conference, ICAIS 2011, Proceedings
Pages40-51
Number of pages12
DOIs
Publication statusPublished - 2011
Event2nd International Conference on Adaptive and Intelligent Systems, ICAIS 2011 - Klagenfurt, Austria
Duration: 6 Sept 20118 Sept 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6943 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference2nd International Conference on Adaptive and Intelligent Systems, ICAIS 2011
Country/TerritoryAustria
CityKlagenfurt
Period6/09/118/09/11

Keywords

  • Adaptive PID
  • Kernel Polarization
  • Multi Kernel
  • Online LSSVR

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