Online Support Vector Regression Based Adaptive NARMA-L2 Controller for Nonlinear Systems
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11063_2020_10403_ReferencePDF.pdf
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Author(s)
Uçak, Kemal
Günel, Gülay Ö.
Date Issued
January 2, 2021
Publisher
Springer US
Version
Author's final manuscript
Abstract
Abstract
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.
MIT Department
Massachusetts Institute of Technology. School of Engineering
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1007/s11063-020-10403-8
