TRMS Experimental Results of New Nonlinear PID Tuned by de Algorithm

Fadi Alyoussef, Ibrahim Kaya

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Scopus citations

Abstract

TRMS is a nonlinear system which resembles a dynamic of a helicopter with a strong coupling effect between main and tail rotors. Generally speaking, the simplicity of the linear PID has tempted the control engineers to use it for controlling the nonlinear systems. However, the linear PID controller could not sufficiently handle these systems particularly in terms of producing a fast response with a small overshoot. Therefore, a new nonlinear PID based on the dynamic of biological cell membrane potentials has been proposed to alleviate the overshoot effect with insuring a small tracking error. The parameters of suggested controller have been tuned by using DE algorithm. The simulation and experimental results have illustrated the superior performance of proposed nonlinear controller compared to a linear PID.

Original languageEnglish
Title of host publicationProceedings - 2019 3rd International Conference on Applied Automation and Industrial Diagnostics, ICAAID 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728128740
DOIs
StatePublished - Sep 2019
Externally publishedYes
Event3rd International Conference on Applied Automation and Industrial Diagnostics, ICAAID 2019 - Elazig, Turkey
Duration: 25 Sep 201927 Sep 2019

Publication series

NameProceedings - 2019 3rd International Conference on Applied Automation and Industrial Diagnostics, ICAAID 2019

Conference

Conference3rd International Conference on Applied Automation and Industrial Diagnostics, ICAAID 2019
Country/TerritoryTurkey
CityElazig
Period25/09/1927/09/19

Bibliographical note

Publisher Copyright:
© 2019 IEEE.

Keywords

  • Differential evolution algorithm
  • Nonlinear PID
  • Nonlinear systems
  • PID
  • TRMS

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering
  • Safety, Risk, Reliability and Quality
  • Control and Optimization

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