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Rotary Flexible Joint Control Using Adaptive Fuzzy Sliding Mode Scheme.

Abdulah Jeza Aljohani1,2, Ibrahim M Mehedi1,2, Muhammad Bilal1,2

  • 1Department of Electrical and Computer Engineering (ECE), King Abdulaziz University, Jeddah 21589, Saudi Arabia.

Computational Intelligence and Neuroscience
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Summary
This summary is machine-generated.

This study introduces an adaptive fuzzy sliding control (AFSMC) method for precise angular position control and vibration reduction in rotary flexible joint systems. The AFSMC approach effectively handles system nonlinearities and uncertainties, ensuring robust performance.

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Area of Science:

  • Robotics and Control Systems
  • Mechanical Engineering
  • Fuzzy Logic Systems

Background:

  • Rotary flexible joint systems present challenges in precise angular position control due to inherent nonlinearities and uncertainties.
  • Vibration suppression is critical for the stable and accurate operation of these systems.
  • Existing control methods may struggle to adapt to dynamic changes and external disturbances.

Purpose of the Study:

  • To develop and evaluate an Adaptive Fuzzy Sliding Control (AFSMC) approach for angular position control and vibration suppression.
  • To enhance the robustness and adaptability of control systems for rotary flexible joints.
  • To demonstrate the effectiveness of AFSMC in handling system nonlinearities, uncertainties, and external perturbations.

Main Methods:

  • The proposed AFSMC combines a fuzzy-based singleton control action with a switching control law.
  • Fuzzy parameters are adjusted using a self-learning mechanism to approximate the ideal feedback linearization control law.
  • Sliding surface and Lyapunov function analysis are employed to prove the closed-loop stability of the AFSMC system.

Main Results:

  • Simulations conducted in MATLAB/Simulink demonstrate the AFSMC's capability in tracking performance.
  • The AFSMC approach effectively compensates for model uncertainties and external perturbations.
  • The control strategy shows satisfactory performance in maintaining desired angular positions and suppressing vibrations.

Conclusions:

  • The AFSMC approach provides a robust and adaptive solution for angular position control and vibration suppression in rotary flexible joint systems.
  • The self-learning capability of the fuzzy parameters allows for effective compensation of system nonlinearities and uncertainties.
  • The proposed control strategy is validated through simulations, confirming its effectiveness and satisfactory tracking performance.