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Experimental Validation of Fuzzy-Optimal Control for a Two-Wheeled Inverted Pendulum

  • Universidad San Francisco de Quito

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

2 Scopus citations

Abstract

This paper presents an optimal controller with integral action based on Takagi-Sugeno (TS) fuzzy modeling of a multivariable nonlinear system to control a two-wheeled inverted pendulum. The T-S fuzzy model was obtained by generating input/output data using Monte Carlo simulations. A Kalman Filter enhances trajectory tracking when estimating the orientation angle, which is problematic due to electromagnetic interference. Furthermore, the Kalman filter is also used to remove the drift effect of the gyro sensor to improve the estimation of the tilt angle. The proposed controller is robust against modeling uncertainties through mass change; it also presents a steady-state error very close to zero, which brings the system to the desired final states. The designed controller was implemented on the Lego Mindstorms NXT 2.0 educational platform using the RobotC programming language.

Original languageEnglish
Title of host publicationECTM 2023 - 2023 IEEE 7th Ecuador Technical Chapters Meeting
EditorsDavid Rivas Lalaleo, Manuel Ignacio Ayala Chauvin
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350338232
DOIs
StatePublished - 2023
Event7th IEEE Ecuador Technical Chapters Meeting, ECTM 2023 - Ambato, Ecuador
Duration: 10 Oct 202313 Oct 2023

Publication series

NameECTM 2023 - 2023 IEEE 7th Ecuador Technical Chapters Meeting

Conference

Conference7th IEEE Ecuador Technical Chapters Meeting, ECTM 2023
Country/TerritoryEcuador
CityAmbato
Period10/10/2313/10/23

Keywords

  • Fuzzy System Identification
  • Kalman Filter
  • Multivariable Control
  • Non-linear Control
  • Optimal Control

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