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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
  • Guang Li

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 & Guang Li, 2022. "Filling Control of a Conical Tank Using a Compact Neuro-Fuzzy Adaptive Control System," Complexity, Hindawi, vol. 2022, pages 1-17, October.
    • Handle: RePEc:hin:complx:4284378
    DOI: 10.1155/2022/4284378
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    Cited by:

    1. Nikolay Didenko & Djamilia Skripnuk & Sergey Barykin & Vladimir Yadykin & Oksana Nikiforova & Angela B. Mottaeva & Valentina Kashintseva & Mark Khaikin & Elmira Nazarova & Ivan Moshkin, 2024. "Impact of Carbon Emission Factors on Economic Agents Based on the Decision Modeling in Complex Systems," Sustainability, MDPI, vol. 16(10), pages 1-14, May.

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