Fuzzy logic with load compensation for upper limb exoskeleton control based on IMU data fusion

Abstract

This paper describes an intelligent control approach for upper limb exoskeleton tracking the user's arm. In this work, the authors critically discuss and compare two different control strategies of PD-Fuzzy and FLC-LC (Fuzzy Logic Controller with Load Compensation) to control an upper limb exoskeleton. Two IMU sensors measure the arm movement of the user, whose data are fed to the developed controller with the goal of achieving a successful interactive control in terms of comfortability, flexibility, and arm motion imitation. To evaluate the performance of these two controllers, two experiments are performed, with and without human-robot interaction. The results show that both control strategies are successful, with the FLC-LC outperforming the PD-Fuzzy in terms of motion tracking and robustness.