Nonlinear Extended Observer-Based ADRC for a Lower-Limb PAM-Based Exoskeleton

Abstract

In lower-limb rehabilitation systems, exoskeleton robots are one of the most important components. These robots help patients to execute repetitive exercises under the guidance of physiotherapists. Recently, pneumatic artificial muscles (PAM), a kind of actuator that acts similarly to human muscles, have been chosen to power the exoskeleton robot for better human–machine interaction. In order to enhance the performance of a PAM-based exoskeleton robot, this article implements an active disturbance rejection control (ADRC) strategy with a nonlinear extended state observer (NLESO). Moreover, the stability of the closed-loop system is proved by Lyapunov’s theory. Finally, the experimental results show that with the proposed control strategy, the rehabilitation robot can effectively track the desired trajectories even when under external disturbance.

Uncertainty-Estimation-Based Prescribed Performance Pressure Control for Train Electropneumatic Brake Systems

“…The extended state observer developed by Jingqing Han can deal with external disturbances and uncertain system dynamics simultaneously [12]. It takes the system uncertainty and disturbances as a new state variable to estimate, and it achieves this without requiring exact model information [13]. For this purpose, the extended state observer has been applied in many practical engineering applications.…”

Neural network based patient recovery estimation of a PAM-based rehabilitation robot

“…As an alternative, the pneumatic artificial muscle (PAM) system has been proposed due to its advantages, including a large power/weight ratio, low cost, lightweight, and similar characteristics to human muscles, as reported in recent studies [3][4][5][6][7][8]. For this reason, a many PAMbased gait training systems have been developed in the literature [8][9][10][11][12][13][14][15][16] that can assist the patient with movement according to the exercises prescribed by the physiotherapist.…”