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dc.contributor.author Jung, Hanul -
dc.contributor.author Oh, Sehoon -
dc.date.accessioned 2023-12-26T18:13:41Z -
dc.date.available 2023-12-26T18:13:41Z -
dc.date.created 2022-08-08 -
dc.date.issued 2022-05-18 -
dc.identifier.isbn 9784886864253 -
dc.identifier.uri http://hdl.handle.net/20.500.11750/46847 -
dc.description.abstract This paper proposes stochastic learning control with disturbance observer and Gaussian process to achieve the robust-ness against disturbance. Disturbance observer is designed from a frequency domain perspective to effectively remove disturbances within a desired range. The Gaussian process stochastically models disturbances that may have high frequency components in the time domain but have a definite period in the position domain. As a result, the synergy between DOB and Gaussian model improves control performance. In addition, the stability of the Gaussian model is theoretically verified and the proposed method is compared under various conditions. © 2022 IEEJ-IAS. -
dc.language English -
dc.publisher Institute of Electrical and Electronics Engineers Inc. -
dc.title Stochastic Learning Control Framework in the Integrated Frequency and Position Domain -
dc.type Conference Paper -
dc.identifier.doi 10.23919/IPEC-Himeji2022-ECCE53331.2022.9807014 -
dc.identifier.scopusid 2-s2.0-85134220535 -
dc.identifier.bibliographicCitation 2022 International Power Electronics Conference, IPEC-Himeji 2022-ECCE Asia, pp.1326 - 1331 -
dc.identifier.url https://www.ipec2022.org/files/IPEC2022_TechnicalProgram.pdf?220513_2 -
dc.citation.conferencePlace JA -
dc.citation.conferencePlace Himeji -
dc.citation.endPage 1331 -
dc.citation.startPage 1326 -
dc.citation.title 2022 International Power Electronics Conference, IPEC-Himeji 2022-ECCE Asia -
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Department of Robotics and Mechatronics Engineering MCL(Motion Control Lab) 2. Conference Papers

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