Neuro-modelling and fuzzy logic control of a two-wheeled wheelchair system
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....
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SAGE Publications Ltd
2024
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| オンライン･アクセス: | http://umpir.ump.edu.my/id/eprint/43915/1/Neuro-modelling%20and%20fuzzy%20logic%20control%20of%20a%20two-wheeled%20wheelchair%20system.pdf http://umpir.ump.edu.my/id/eprint/43915/ https://doi.org/10.1177/14613484241287608 https://doi.org/10.1177/14613484241287608 |
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my.ump.umpir.439152025-02-26T03:08:28Z http://umpir.ump.edu.my/id/eprint/43915/ 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 Tokhi, M. Osman TK Electrical engineering. Electronics Nuclear engineering 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. SAGE Publications Ltd 2024 Article PeerReviewed pdf en cc_by_4 http://umpir.ump.edu.my/id/eprint/43915/1/Neuro-modelling%20and%20fuzzy%20logic%20control%20of%20a%20two-wheeled%20wheelchair%20system.pdf Nizaruddin, M. Nasir and Nor Maniha, Abdul Ghani and Ahmad Nor Kasruddin, Nasir and Mohd Ashraf, Ahmad and Tokhi, M. Osman (2024) Neuro-modelling and fuzzy logic control of a two-wheeled wheelchair system. Journal of Low Frequency Noise, Vibration and Active Control. pp. 1-15. ISSN 1461-3484 (Print), 2048-4046 (Online). (In Press / Online First) (In Press / Online First) https://doi.org/10.1177/14613484241287608 https://doi.org/10.1177/14613484241287608 |
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| language |
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| topic |
TK Electrical engineering. Electronics Nuclear engineering |
| spellingShingle |
TK Electrical engineering. Electronics Nuclear engineering Nizaruddin, M. Nasir Nor Maniha, Abdul Ghani Ahmad Nor Kasruddin, Nasir Mohd Ashraf, Ahmad Tokhi, M. Osman Neuro-modelling and fuzzy logic control of a two-wheeled wheelchair system |
| description |
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. |
| format |
Article |
| author |
Nizaruddin, M. Nasir Nor Maniha, Abdul Ghani Ahmad Nor Kasruddin, Nasir Mohd Ashraf, Ahmad Tokhi, M. Osman |
| author_facet |
Nizaruddin, M. Nasir Nor Maniha, Abdul Ghani Ahmad Nor Kasruddin, Nasir Mohd Ashraf, Ahmad Tokhi, M. Osman |
| author_sort |
Nizaruddin, M. Nasir |
| title |
Neuro-modelling and fuzzy logic control of a two-wheeled wheelchair system |
| title_short |
Neuro-modelling and fuzzy logic control of a two-wheeled wheelchair system |
| title_full |
Neuro-modelling and fuzzy logic control of a two-wheeled wheelchair system |
| title_fullStr |
Neuro-modelling and fuzzy logic control of a two-wheeled wheelchair system |
| title_full_unstemmed |
Neuro-modelling and fuzzy logic control of a two-wheeled wheelchair system |
| title_sort |
neuro-modelling and fuzzy logic control of a two-wheeled wheelchair system |
| publisher |
SAGE Publications Ltd |
| publishDate |
2024 |
| url |
http://umpir.ump.edu.my/id/eprint/43915/1/Neuro-modelling%20and%20fuzzy%20logic%20control%20of%20a%20two-wheeled%20wheelchair%20system.pdf http://umpir.ump.edu.my/id/eprint/43915/ https://doi.org/10.1177/14613484241287608 https://doi.org/10.1177/14613484241287608 |
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1827518417096146944 |
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13.251813 |