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<p>The dexterity of the human hand is largely due to its multiple degrees of freedom. However, coordinating the movements of the ring and little fingers independently can be challenging because of the biomechanical and neurological interdependencies between them. This research presents a cascade control system based on fuzzy logic to manage the dynamic movements of these fingers within a simulated biomechanical model of a human hand. A mathematical model that incorporates transfer functions and state-space representations has been developed for the fingers. The fuzzy logic controller is designed to address the nonlinearity of the biomechanical model, optimizing both the transient and steady-state response parameters. The simulation results indicate that the system achieves a rise time of 0.6&#xa0;s and a peak time of 0.3&#xa0;s for the ring finger, with an overshoot of 5%. The little finger, on the other hand, exhibits an overshoot of less than 0.6% and a settling time ranging from 1 to 2.6&#xa0;s across various joints. Overall, the proposed control system successfully coordinates finger movements, achieving a stable response within 3.5&#xa0;s and minimal disturbances. These findings represent significant advancements in precision and robustness for prosthetic and robotic hand systems, providing a promising foundation for assistive technologies aimed at fine motor control rehabilitation.</p>

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Optimal position fuzzy control for coordinated movement of the ring and little fingers in an impaired human hand

  • 期刊论文

  • 发表日期：

    2025年9月5日

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  • Maryam Iqbal,
  • Sabtain Rasool

摘要

The dexterity of the human hand is largely due to its multiple degrees of freedom. However, coordinating the movements of the ring and little fingers independently can be challenging because of the biomechanical and neurological interdependencies between them. This research presents a cascade control system based on fuzzy logic to manage the dynamic movements of these fingers within a simulated biomechanical model of a human hand. A mathematical model that incorporates transfer functions and state-space representations has been developed for the fingers. The fuzzy logic controller is designed to address the nonlinearity of the biomechanical model, optimizing both the transient and steady-state response parameters. The simulation results indicate that the system achieves a rise time of 0.6 s and a peak time of 0.3 s for the ring finger, with an overshoot of 5%. The little finger, on the other hand, exhibits an overshoot of less than 0.6% and a settling time ranging from 1 to 2.6 s across various joints. Overall, the proposed control system successfully coordinates finger movements, achieving a stable response within 3.5 s and minimal disturbances. These findings represent significant advancements in precision and robustness for prosthetic and robotic hand systems, providing a promising foundation for assistive technologies aimed at fine motor control rehabilitation.