A linear discrete-time extended state observer-based intelligent PD controller for a 12 DOFs lower limb exoskeleton LLE-RePA. (April 2020)

• Record Type: Journal Article
• Authors: Han, Shuaishuai; Wang, Haoping; Tian, Yang
• Is Part Of: Mechanical systems and signal processing. Volume 138(2020)
• Publication Date: 2020-04
• Subjects: Lower limb exoskeleton -- Model free control -- Intelligent PD -- Linear discrete-time extended state observer -- Sigmoid function-based tracking differentiator; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2019.106547
• Languages: English
• ISSNs: 0888-3270

Abstract

Highlights: A LDESO based iPD controller with STD is proposed for LLE-RePA. A 12 DOF exoskeleton LLE-RePA is designed for limb rehabilitation and power augmentation. LDESO is utilized to estimate the lumped disturbance in ultra-local model. STD is used to obtain the desire velocity and acceleration valueFor digital application, the controller is designed in discrete and the stability analysis is given. Compared to conventional PD controller, high performances on LLE-RePA control are validated. Abstract: To perform the motion control of a 12 DOFs lower limb exoskeleton for rehabilitation and power augmentation (LLE-RePA), this paper proposes a linear discrete-time extended state observer (LDESO) based intelligent PD (iPD) controller with sigmoid function-based tracking differentiator (STD). A three-order discrete-time STD is designed to obtain smooth real-time reference velocity and acceleration signal. The adopted iPD controller is a kind of model free method based on ultra-local model, which formulates complex human-exoskeleton dynamics in a simple way and make closed-loop PD parameters easy to be tuned. The LDESO is utilized to estimate and eliminate the lumped total disturbance in ultra-local model which contains unknown model dynamics and unpredictable human-exoskeleton interaction influence. The estimation result of LDESO is used to compensate the control input. Simulation and experimental results with exoskeleton LLE-RePA demonstrate the high performance of the proposed method.