Online Support Vector Regression Based Adaptive NARMA-L2 Controller for Nonlinear Systems

Kemal Uçak*, Gülay Öke Günel

*Bu çalışma için yazışmadan sorumlu yazar

Araştırma sonucu: Dergiye katkıMakalebilirkişi

12 Atıf (Scopus)

Özet

NARMA model is a simple and effective way to represent nonlinear systems, based on the NARMA model, NARMA-L2 controller is designed and has been successfully applied in the literature. Success of NARMA-L2 controller is directly related to the precision with which controlled systems’ dynamics can be estimated. In this paper, online SVR is utilized to obtain controlled plant’s subdynamics and consequently this information is used in the construction of NARMA-L2 controller. Hence functionality of NARMA-L2 controllers and high generalization capability of SVR are combined. Also, SVR formulates a convex optimization problem and therefore guarantees global optimum solution. The proposed method is assessed by performing simulations on a nonlinear CSTR system, the robustness of the designed controller is also tested under noisy and uncertainty conditions.

Orijinal dilİngilizce
Sayfa (başlangıç-bitiş)405-428
Sayfa sayısı24
DergiNeural Processing Letters
Hacim53
Basın numarası1
DOI'lar
Yayın durumuYayınlandı - Şub 2021

Bibliyografik not

Publisher Copyright:
© 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature.

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