Improving Disturbance Rejection Capability for a Quadcopter UAV System Using Self-Regulating Fuzzy PID Controller

Sherif I. Abdelmaksoud, Musa Mailah, Ayman M. Abdallah

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

4 Scopus citations

Abstract

The quadcopter model is one of the most versatile flying machines nowadays. However, it is an under-Actuated, highly non-linear, and coupling system. It is also sensitive to external disturbances and uncertainties while trajectory tracking. Thus, in this study, a robust control method for the quadcopter system was proposed to improve system stability and disturbances rejection capability by utilizing a Self-Regulating (SR) Fuzzy Proportional-Integral-Derivative (FPID) control system, to be known as (SR-FPID) scheme. The proposed control system was designed based on the Fuzzy Logic (FL) to provide the automatic tuning of the PID control parameters based on various operating and loading requirements. The simulated results reveal the efficiency and robustness of the SR-FPID scheme in significantly improving the disturbance rejection capability and reducing the percentages of the settling time and the peak time of at least 97% in the presence of various forms of external perturbations.

Original languageEnglish
Title of host publicationProceedings of
Subtitle of host publication2020 International Conference on Computer, Control, Electrical, and Electronics Engineering, ICCCEEE 2020
EditorsDalia Mahmoud, Siddig Gomha, Atif Osman
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728191119
DOIs
StatePublished - 26 Feb 2021

Publication series

NameProceedings of: 2020 International Conference on Computer, Control, Electrical, and Electronics Engineering, ICCCEEE 2020

Bibliographical note

Publisher Copyright:
© 2021 IEEE.

Keywords

  • Disturbance Rejection
  • Fuzzy logic
  • PID
  • Quadcopter
  • Rotorcraft UAVs
  • Self-regulating
  • Trajectory tracking

ASJC Scopus subject areas

  • Artificial Intelligence
  • Hardware and Architecture
  • Energy Engineering and Power Technology
  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Control and Optimization
  • Instrumentation

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