An Intelligent PID Controller Based on Ultra-Local Model for Trajectory Tracking in Lower Limb Exoskeleton Robot

Abstract

Aiming to enhance trajectory tracking for lower limb exoskeleton (LLEX) robot, this study proposes an intelligent proportional, integral, derivative (iPID) controller based ultra-local model (ULM) to achieve precise trajectory tracking for LLEX, moreover to optimize the controller performance, the particle swarm optimization (PSO) is utilized for controller gains tuning. The LLEX robot with four degrees of freedom (4-DOF) is created using SOLIDWORKS software and then transferred to MATLAB/SIMULINK for simulation and control purposes. Compared with the conventional proportional, integral, derivative (PID) controller, the iPID controller reduced trajectory tracking errors while achieving faster time convergence of less than 0.0001 and 0.00012 seconds for the hip and knee joints, respectively. Specifically, the estimated root mean square (RMS) of the tracking error for the hip and knee joints were 0.0012 and 0.013, respectively, indicating smaller error values achieved by the iPID based ULM model. This performance was further confirmed using integral time absolute error (ITAE), and integral absolute of the error (IAE) metrics. Based on the results obtained, it can be concluded that the iPID-based ULM model outperformed the conventional PID controller and has the potential to improve trajectory tracking for the LLEX robot.