Adaptive control based on an on-line parameter estimation of an upper limb exoskeleton

Area of Science:

• Robotics
• Biomechanics
• Control Systems

Background:

• Exoskeleton control is challenged by unknown and variable human limb dynamics.
• Inconsistent dynamic parameters degrade the performance of human-exoskeleton control systems.
• Adaptive control strategies are needed to ensure robust exoskeleton performance.

Purpose of the Study:

• To enhance the control performance of upper-limb exoskeletons for patient assistance.
• To address challenges posed by unknown and person-specific human limb dynamic parameters.
• To develop an adaptive control strategy incorporating an online dynamic parameter estimator.

Main Methods:

• An adaptive control strategy is proposed, featuring a supplementary loop with an online dynamic parameter estimator.
• A physical model of the exoskeleton interacting with a 7 Degree of Freedom (DoF) upper limb model was generated using SimMechanics (Matlab/Simulink).
• The controller's parameter adaptation ensures system performance despite parameter uncertainties and perturbations.

Main Results:

• The proposed adaptive control strategy effectively improves exoskeleton control performance.
• The online dynamic parameter estimator successfully adapts controller parameters in real-time.
• Simulations demonstrated the system's ability to maneuver the exoskeleton for passive rehabilitation movements.

Conclusions:

• The adaptive control strategy with an online dynamic parameter estimator is effective for upper-limb exoskeletons.
• This approach enhances rehabilitation by enabling precise tracking of desired trajectories for passive arm movements.
• The method offers improved robustness against human limb dynamic variations.