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Filling Control of a Conical Tank Using a Compact Neuro‐Fuzzy Adaptive Control System

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  • Helbert Espitia-Cuchango
  • Iván Machón-González
  • Hilario López-García

Abstract

This document describes the implementation of a conical tank control system using an adaptive neurofuzzy system. For implementation, an indirect approach is used where the controller is optimized using the model obtained during the plant identification carried out using data obtained during the system operation. Furthermore, implementation includes training of neuro fuzzy‐systems and application to control a conical tank. Regarding plant identification, preliminary training takes place using data obtained for different input values. The controller configuration is established considering the analogy with a discrete‐time linear system. The simulation shows that the control system manages to approach the desired response given by the considered reference model.

Suggested Citation

  • Helbert Espitia-Cuchango & Iván Machón-González & Hilario López-García, 2022. "Filling Control of a Conical Tank Using a Compact Neuro‐Fuzzy Adaptive Control System," Complexity, John Wiley & Sons, vol. 2022(1).
    • Handle: RePEc:wly:complx:v:2022:y:2022:i:1:n:4284378
    DOI: 10.1155/2022/4284378
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    References listed on IDEAS

    as
    1. Hua Zhang & Shenggang Li, 2021. "Fuzzy Adaptive Control of Uncertain MIMO Chaotic Systems with Unknown Control Direction," Complexity, Hindawi, vol. 2021, pages 1-9, May.
    2. Zhao Zhang & Zhong Yang & Si Xiong & Shuang Chen & Shuchang Liu & Xiaokai Zhang & Danilo Comminiello, 2021. "Simple Adaptive Control-Based Reconfiguration Design of Cabin Pressure Control System," Complexity, Hindawi, vol. 2021, pages 1-16, March.
    3. Wei Guan & Haotian Zhou & Zuojing Su & Xianku Zhang & Chao Zhao, 2019. "Ship Steering Control Based on Quantum Neural Network," Complexity, Hindawi, vol. 2019, pages 1-10, December.
    4. Helbert Eduardo Espitia & Iván Machón-González & Hilario López-García & Guzmán Díaz, 2019. "Proposal of an Adaptive Neurofuzzy System to Control Flow Power in Distributed Generation Systems," Complexity, Hindawi, vol. 2019, pages 1-16, March.
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