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Design of an Adaptive Support Vector Regressor Controller for a Spherical Tank System

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Neural Information Processing (ICONIP 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9491))

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Abstract

In this study, an adaptive support vector regressor (SVR) controller which has previously been proposed [1] is applied to control the liquid level in a spherical tank system. The variations in the cross sectional area of the tank depending on the liquid level is the main cause of nonlinearity in system. The parameters of the controller are optimized depending on the future behaviour of the system which is approximated via a seperate online SVR model of the system. In order to adjust controller parameters, the “closed-loop margin” which is calculated using the tracking error has been optimized. The performance of the proposed method has been examined by simulations carried out on a nonlinear spherical tank system, and the results reveal that the SVR controller together with SVR model leads to good tracking performance with small modeling, transient state and steady state errors.

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Authors and Affiliations

  1. Faculty of Electrical-Electronics, Department of Control and Automation Engineering, Istanbul Technical University, Ayazaga Campus, 34469, Istanbul, Turkey

    Kemal Uçak & Gülay Öke Günel

Authors
  1. Kemal Uçak
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  2. Gülay Öke Günel
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Corresponding author

Correspondence to Kemal Uçak .

Editor information

Editors and Affiliations

  1. University of Istanbul, Istanbul, Turkey

    Sabri Arik

  2. University at Qatar, Doha, Qatar

    Tingwen Huang

  3. Tunku Abdul Rahman University College, Kuala Lumpur, Malaysia

    Weng Kin Lai

  4. University of Science Technology, Wuhan, China

    Qingshan Liu

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Uçak, K., Öke Günel, G. (2015). Design of an Adaptive Support Vector Regressor Controller for a Spherical Tank System. In: Arik, S., Huang, T., Lai, W., Liu, Q. (eds) Neural Information Processing. ICONIP 2015. Lecture Notes in Computer Science(), vol 9491. Springer, Cham. https://doi.org/10.1007/978-3-319-26555-1_1

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  • DOI: https://doi.org/10.1007/978-3-319-26555-1_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-26554-4

  • Online ISBN: 978-3-319-26555-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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