Work

Error-Accumulation Improved Newton Algorithm in Model Predictive Control for Novel Compliant Actuator-Driven Upper-Limb Exoskeleton

Year: 2025

Type: article

Abstract: In this paper, a Novel Compliant Actuator (NCA)-driven Upper-Limb Exoskeleton (ULE) with force controllable, impact resistance, and back drivability is designed to ensure the safety of the subject during Human-Robot Interaction (HRI) processing. Based on the designed NCA-driven ULE, this paper constructs a Model Predictive Control Scheme (MPCS) for force trajectory tracking, which minimises future tracking errors by solving an optimal control problem with inequality constraints. In addition, an Error-Accumulation Improved Newton Algorithm (EAINA) is proposed to solve the MPCS for suppressing various noises and external disturbances. The proposed EAINA is theoretically proved to have small steady state for noise conditions and stability of the EAINA using Lyapunov method. Finally, experimental results verify that the proposed MPCS solved by the EAINA in the NCA-driven ULE achieves robustness, fast convergence, strong tolerance and stability for trajectory rehabilitation task.

Source: Tsinghua Science & Technology

DOI: 10.26599/tst.2024.9010145

Authors: Changxian Xu, Jiliang Zhang, Keping Liu, Jian Wang, Zhongbo Sun

Institutions: Changchun University of Technology, Northeastern University, Jilin Engineering Normal University, Chinese Academy of Sciences, Institute of Automation

Language: English

Topic: Prosthetics and Rehabilitation Robotics

Subfield: Biomedical Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: diamond

Funder: National Natural Science Foundation of China