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

Journal of Robotics and Control (JRC) · Vol. 7 No. 2 (2026) · hlm. 3598–3610

DOI
10.18196/jrc.v7i2.28562
ISSN
2715-5072, 2715-5056
Terbit
2026-03-01
Penerbit
Universitas Muhammadiyah Yogyakarta
Bahasa
eng
Lisensi
creativecommons.org/licenses/by-sa/4.0

Abstrak

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.

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  • National Research and Innovation Agency
  • Institut Teknologi Sepuluh Nopember
  • Politeknik Elektronika Negeri Surabaya
  • Tampere University
  • University of Indonesia
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Rekan penulisOrganisasiArtikel bersama
Jalu A. PrakosaNational Research and Innovation Agency2
Enggar Banifa PratiwiNational Research and Innovation Agency2
Haniah MahmudahInstitut Teknologi Sepuluh Nopember1
Syamsul ArifinPoliteknik Elektronika Negeri Surabaya1
Catur Arif PrastyantoInstitut Teknologi Sepuluh Nopember1
Harry SeptantoNational Research and Innovation Agency1
Samsul HafizNational Research and Innovation Agency1
Made Widhi Surya AtmanTampere University1
Oetomo SudjanaAfiliasi tidak diketahui1
Hendra AdinantaNational Research and Innovation Agency1
Suryadi SuryadiNational Research and Innovation Agency1
Purwowibowo PurwowibowoNational Research and Innovation Agency1
Sensus WijonarkoNational Research and Innovation Agency1
Tatik MaftukhahNational Research and Innovation Agency1
Dadang RustandiNational Research and Innovation Agency1
Mahmudi MahmudiNational Research and Innovation Agency1
Prawito PrajitnoUniversity of Indonesia1
Mat Syai’inInstitut Teknologi Sepuluh Nopember1
Syamsul ArifinInstitut Teknologi Sepuluh Nopember1
Syamsiar KautsarInstitut Teknologi Sepuluh Nopember1

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Sumber metadata: OAI-PMH (metadata jurnal) https://journal.umy.ac.id/index.php/jrc/oai, pertama di-harvest 9 Nov 2026, terakhir terlihat 9 Nov 2026.
Metadata asli (oai_dc) 
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	<dc:title xml:lang="en-US">Enhanced General Modified Repetitive Control Design for 1-DOF Lower Limb Exoskeleton</dc:title>
	<dc:creator>Rahmatillah, Akif</dc:creator>
	<dc:creator>Siti Aisjah, Aulia</dc:creator>
	<dc:creator>Suyanto</dc:creator>
	<dc:creator>Kurniawan, Edi</dc:creator>
	<dc:subject xml:lang="en-US">repetitive control</dc:subject>
	<dc:subject xml:lang="en-US">lower-limb exoskeleton</dc:subject>
	<dc:subject xml:lang="en-US">linear matrix inequality</dc:subject>
	<dc:subject xml:lang="en-US"> error state-variable</dc:subject>
	<dc:subject xml:lang="en-US">tracking performance</dc:subject>
	<dc:description xml:lang="en-US">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.</dc:description>
	<dc:publisher xml:lang="en-US">Universitas Muhammadiyah Yogyakarta</dc:publisher>
	<dc:date>2026-03-01</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journal.umy.ac.id/index.php/jrc/article/view/28562</dc:identifier>
	<dc:identifier>10.18196/jrc.v7i2.28562</dc:identifier>
	<dc:source xml:lang="en-US">Journal of Robotics and Control (JRC); Vol. 7 No. 2 (2026); 3598-3610</dc:source>
	<dc:source>2715-5072</dc:source>
	<dc:source>2715-5056</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journal.umy.ac.id/index.php/jrc/article/view/28562/12481</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2026 Akif Rahmatillah, Aulia Siti Aisjah, Suyanto, Edi Kurniawan</dc:rights>
	<dc:rights xml:lang="en-US">https://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>