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dc.contributor.author
Lu, Peng
dc.contributor.author
Sandy, Timothy
dc.contributor.author
Buchli, Jonas
dc.date.accessioned
2020-09-03T08:42:57Z
dc.date.available
2020-09-03T08:42:57Z
dc.date.issued
2019
dc.identifier.isbn
978-1-7281-4004-9
en_US
dc.identifier.isbn
978-1-7281-4003-2
en_US
dc.identifier.isbn
978-1-7281-4005-6
en_US
dc.identifier.issn
21530866
dc.identifier.other
10.1109/IROS40897.2019.8970476
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/438203
dc.description.abstract
This paper presents a novel nonlinear disturbance rejection approach for high precision model-based control of hydraulic robots. While most disturbance rejection approaches make use of observers, we propose a novel adaptive Unscented Kalman Filter to estimate the disturbances in an unbiased minimum-variance sense. The filter is made adaptive such that there is no need to tune the covariance matrix for the disturbance estimation. Furthermore, whereas most model-based control approaches require the linearization of the system dynamics, our method is nonlinear which means that no linearization is required. Through extensive simulations as well as real hardware experiments, we demonstrate that our proposed approach can achieve high precision tracking and can be readily applied to most robotic systems even in the presence of uncertainties and external disturbances. The proposed approach is also compared to existing approaches which demonstrates its superior tracking performance.
en_US
dc.language.iso
en
en_US
dc.publisher
IEEE
en_US
dc.title
Adaptive Unscented Kalman Filter-based Disturbance Rejection With Application to High Precision Hydraulic Robotic Control
en_US
dc.type
Conference Paper
dc.date.published
2020-01-27
ethz.book.title
2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
en_US
ethz.pages.start
4365
en_US
ethz.pages.end
4372
en_US
ethz.event
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2019)
en_US
ethz.event.location
Macau, China
en_US
ethz.event.date
November 3-8, 2019
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.publication.place
Piscataway, NJ
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02100 - Dep. Architektur / Dep. of Architecture::02284 - NFS Digitale Fabrikation / NCCR Digital Fabrication
ethz.date.deposited
2020-03-18T02:41:10Z
ethz.source
SCOPUS
ethz.source
WOS
ethz.eth
yes
en_US
ethz.availability
Metadata only
en_US
ethz.rosetta.installDate
2020-09-03T08:43:09Z
ethz.rosetta.lastUpdated
2020-09-03T08:43:09Z
ethz.rosetta.versionExported
true
dc.identifier.olduri
http://hdl.handle.net/20.500.11850/405495
dc.identifier.olduri
http://hdl.handle.net/20.500.11850/431519
ethz.COinS
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