Neuro-modelling and fuzzy logic control of a two-wheeled wheelchair system

NIzaruddin M. Nasir, Nor Maniha Abdul Ghani, Ahmad Nor Kasruddin Nasir, Mohd Ashraf Ahmad, Mohammad Osman Tokhi

Research output: Contribution to journalArticlepeer-review

Abstract

Two-wheeled wheelchairs have been used as alternatives for the elderly and disabled people to perform physical activities due to their restriction of movement. Significant challenges posed by two-wheeled wheelchairs control due to their inherent instability, resembling that inverted pendulum system. This research addresses these challenges by developing a dynamic non-linear model and stability control using computational algorithms. A neural network-based Nonlinear Autoregressive model with Exogenous Inputs (NARX) was developed, capturing and behaving similar to the complex dynamics of the wheelchair system with the identification on the experimental input–output data. Ensuring stable and responsive control, design of optimized PD-type and PID-type fuzzy logic controllers using Particle Swarm Optimization (PSO) were established and were tested under a simulation environment. The performance was evaluated across various metrics, including Integral Squared Error (ISE), Integral Absolute Error (IAE), Mean Squared (MSE), and Integral Time Absolute Error (ITAE). The result demonstrates that the PSO Optimized PID-type fuzzy logic controller with scaling factor from MSE index performance come out as best overall, significantly outperforms PD-type fuzzy logic controller, reducing its settling time by 12.5% to 35 s, minimizing overshoot to 0.81°, and achieving a negligible steady-state error of 0.046%. These results highlight the significant of integrating fuzzy logic control and PSO to the neural network model in enhancing the stability and performance of two-wheeled wheelchair systems, offering user safety and comfort.
Original languageEnglish
Number of pages15
JournalJournal of Low Frequency Noise Vibration and Active Control
Early online date18 Oct 2024
DOIs
Publication statusE-pub ahead of print - 18 Oct 2024
Externally publishedYes

Bibliographical note

Publisher Copyright:
© The Author(s) 2024.

Keywords

  • Neural network
  • fuzzy logic control
  • particle swarm optimization
  • system identification
  • two-wheeled wheelchair

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