Design of Adaptive PID Controller for Lower Limb Exoskeleton Robot Based on Improved Black Hole Optimization

Abstract

Lower limb exoskeleton robots have gained considerable attention in the field of rehabilitation. The effectiveness of these systems depends on the precision and adaptability of their control mechanisms. This study presents a novel approach to enhance the performance of lower limb exoskeleton robots through the design of an adaptive Proportional-Integral-Derivative (PID) controller, coupled with the tuning of its parameters using an Improved Black Hole Optimization (IBHO) algorithm. The proposed adaptive control strategy aims to enable the exoskeleton robot to efficiently adapt to the dynamic and diverse movement requirements of different users, thereby improving the overall user experience and system efficacy. The IBHO algorithm is employed to optimize the PID controller parameters, applying its superior exploration and exploitation capabilities to achieve optimal tuning in a computationally efficient manner. The effectiveness of the designed adaptive PID controller is validated through simulations results on a lower limb exoskeleton robot prototype. Results demonstrate the significant improvements in tracking accuracy, and adaptability to varying walking patterns and user dynamics.