Rotary Flexible Joint Control Using Adaptive Fuzzy Sliding Mode Scheme.

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.