Model free adaptive support vector regressor controller for nonlinear systems

Kemal Uçak*, Gülay Öke Günel

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

15 Citations (Scopus)

Abstract

In this study, a novel model free support vector regressor controller (MF-SVR controller ) is introduced for nonlinear dynamical systems. For the adaptation mechanism, a model free closed-loop margin which is a function of tracking error is derived and it is used to optimize the parameters of MF-SVR controller . The effectiveness of the adjustment mechanism and closed-loop performance of the MF-SVR controller have been examined by simulations performed on continuously stirred tank reactor (CSTR) and bioreactor benchmark systems. In order to observe the impacts of the removal of the model estimation block in control architecture, the performance of the MF-SVR controller is compared with a model based support vector regressor controller (MB-SVR controller ) and SVM-based PID controller. The results indicate that MF-SVR controller diminishes the computational load of MB-SVR controller at the cost of a small amount of decrease in tracking performance.

Original languageEnglish
Pages (from-to)47-67
Number of pages21
JournalEngineering Applications of Artificial Intelligence
Volume81
DOIs
Publication statusPublished - May 2019

Bibliographical note

Publisher Copyright:
© 2019 Elsevier Ltd

Keywords

  • Adaptive control
  • Direct adaptive control
  • Model free adaptive control(MFAC)
  • Model free SVR controller
  • Online support vector regression
  • SVR controller

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