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Customizing a Cryolite Glass Prosthetic Eye
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Innovative approach of nonlinear controllers design for prosthetic knee performance.

Atif Rehman1, Rimsha Ghias2, Hammad Iqbal Sherazi3

  • 1School of Interdisciplinary Engineering and Sciences, National University of Sciences and Technology, Islamabad, Pakistan.

Frontiers in Neurorobotics
|February 6, 2026
PubMed
Summary

This study introduces advanced nonlinear control strategies for prosthetic knee joints, optimizing gait for individuals with lower-limb loss. The CoBA-based controller showed superior performance in simulations and hardware tests.

Keywords:
Lyapunov stabilityadaptive barrier functionhardware-in-looplower-limb biomechanicsnonlinear controlprosthetic knee jointreal-time controlsliding mode control

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Area of Science:

  • Robotics and biomechatronics
  • Control systems engineering
  • Biomedical engineering

Background:

  • Prosthetic knee joints are crucial for restoring mobility in individuals with lower-limb loss.
  • Existing prosthetic knees face challenges with nonlinear dynamics, disturbances, and uncertainties during locomotion.
  • Advanced control strategies are needed to improve the naturalness and adaptability of prosthetic gait.

Purpose of the Study:

  • To develop and evaluate novel nonlinear control strategies for a two-degree-of-freedom prosthetic knee joint.
  • To optimize controller parameters using the Red Fox Optimization algorithm.
  • To validate the proposed control framework through simulation and hardware-in-the-loop testing.

Main Methods:

  • Development of a comprehensive nonlinear dynamic model for a prosthetic knee.
  • Implementation of three robust nonlinear controllers: Integral Sliding Mode Control, Conditional Super-Twisting Sliding Mode Control, and Conditional Adaptive Positive Semidefinite Barrier Function-based Sliding Mode Control (CoBA).
  • Parameter optimization using Red Fox Optimization and stability analysis via Lyapunov theory.
  • Simulation in MATLAB/Simulink and hardware-in-the-loop validation using a C2000 Delfino F28379D microcontroller.

Main Results:

  • The CoBA-based controller demonstrated superior tracking accuracy, faster convergence, and a smoother torque profile compared to other methods.
  • Stability analysis confirmed the robustness of the controllers under various conditions.
  • Simulations and hardware experiments showed close agreement, validating the practical applicability of the control framework.

Conclusions:

  • The proposed nonlinear control strategies, particularly the CoBA approach, offer a significant advancement in prosthetic knee control.
  • The Red Fox Optimization algorithm effectively tuned controller parameters for enhanced performance.
  • The validated control framework provides a promising foundation for developing intelligent and adaptive prosthetic knee systems.