A New Impedance Controller Based on Nonlinear Model Reference Adaptive Control for Exoskeleton Systems

Kai Gui, Honghai Liu, Dingguo Zhang

Research output: Contribution to journalArticle

Abstract

Robotic exoskeletons are expected to show high compliance and low impedance for human-robot interactions (HRIs). Our study introduces a novel method based on nonlinear model reference adaptive control (MRAC) to reduce the inherent impedance and replace the traditional impedance controller in HRIs. The control law and adaptive law are designed according to a candidate Lyapunov function. A simple system identification and initialization method for the nonlinear MRAC is put forward, which provides a set of better initial values for the controller. From the results of simulation and experiment, our controller can reduce the mechanical impedance and achieve high compliance for HRI. The adaptive control and compliance control can be both achieved by the proposed nonlinear MRAC framework.

Original languageEnglish
Article number1950020
JournalInternational Journal of Humanoid Robotics
Volume16
Issue number5
DOIs
Publication statusPublished - 2 Aug 2019

Keywords

  • Human-robot interaction
  • compliance control
  • nonlinear model reference adaptive control
  • robotic exoskeleton
  • system identification

ASJC Scopus subject areas

  • Mechanical Engineering
  • Artificial Intelligence

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