Skip to main navigation Skip to search Skip to main content

Enhanced General Modified Repetitive Control Design for 1-DOF Lower Limb Exoskeleton

  • Department of Engineering Physics
  • Institut Teknologi Sepuluh Nopember
  • National Research and Innovation Agency Republic of Indonesia
  • Research Center for Photonics

Research output: Contribution to journal › Article › peer-review

Abstract

—This paper introduces an Enhanced Generalized Modified Repetitive Control (EGMRC) scheme in which the compensator is derived directly in the continuous-time domain, avoiding conversion to a two-dimensional hybrid model. The proposed method is implemented for angular position tracking of a 1-DOF lower-limb robotic exoskeleton driven by a periodic reference. The closed-loop dynamics are expressed in an error-state form to explicitly capture the tracking objective. Controller gains are determined via linear matrix inequality (LMI) conditions to ensure asymptotic stability, while performance is shaped by tuning the relative contributions of the control and learning actions and by adjusting the internal-model filter cut-off frequency. Numerical studies verify the proposed approach and show that the most accurate tracking is obtained when the learning-action gain exceeds the control-action gain. The results further suggest that increasing the internal-model cut-off frequency generally improves tracking accuracy. Compared with generalized repetitive control (GRC), EGMRC achieves superior performance in the evaluated metrics, with the exception of settling time.

Original languageEnglish
Pages (from-to)3598-3610
Number of pages13
JournalJournal of Robotics and Control (JRC)
Volume7
Issue number2
DOIs
Publication statusPublished - 20 May 2026

Keywords

  • error state-variable
  • linear matrix inequality
  • lower-limb exoskeleton
  • tracking performance
  • —repetitive control

Fingerprint

Dive into the research topics of 'Enhanced General Modified Repetitive Control Design for 1-DOF Lower Limb Exoskeleton'. Together they form a unique fingerprint.

Cite this