An Extended Robust H inftyFilter for Nonlinear Constrained Uncertain Systems
In this correspondence, a robust filter is proposed to effectively estimate the system states in the case where system model uncertainties as well as disturbances are present. The proposed robust filter is constructed based on the linear approximation methods for a general nonlinear uncertain system...
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| Veröffentlicht in: | IEEE transactions on signal processing 2006-11, Vol.54 (11), p.4471-4475 |
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| container_end_page | 4475 |
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| container_issue | 11 |
| container_start_page | 4471 |
| container_title | IEEE transactions on signal processing |
| container_volume | 54 |
| creator | Jaewon Seo Myeong-Jong Yu Chan Gook Park Jang Gyu Lee |
| description | In this correspondence, a robust filter is proposed to effectively estimate the system states in the case where system model uncertainties as well as disturbances are present. The proposed robust filter is constructed based on the linear approximation methods for a general nonlinear uncertain system with an integral quadratic constraint. We also derive the important characteristic of the proposed filter, a modified H infin performance index. Analysis results show that the proposed filter has robustness against disturbances such as process and measurement noises, and against parameter uncertainties. Simulation results show that the proposed filter provides a performance improvement |
| doi_str_mv | 10.1109/TSP.2006.880308 |
| format | Article |
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Simulation results show that the proposed filter provides a performance improvement</description><identifier>ISSN: 1053-587X</identifier><identifier>EISSN: 1941-0476</identifier><identifier>DOI: 10.1109/TSP.2006.880308</identifier><identifier>CODEN: ITPRED</identifier><language>eng</language><publisher>IEEE</publisher><subject>Aerospace engineering ; Estimation error ; Extended robust ; Linear approximation ; Noise robustness ; nonlinear estimation ; Nonlinear filters ; Nonlinear systems ; nonlinear uncertain system ; robust estimation ; State estimation ; Statistics ; Uncertain systems ; Uncertainty</subject><ispartof>IEEE transactions on signal processing, 2006-11, Vol.54 (11), p.4471-4475</ispartof><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/1710390$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,796,27924,27925,54758</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/1710390$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Jaewon Seo</creatorcontrib><creatorcontrib>Myeong-Jong Yu</creatorcontrib><creatorcontrib>Chan Gook Park</creatorcontrib><creatorcontrib>Jang Gyu Lee</creatorcontrib><title>An Extended Robust H inftyFilter for Nonlinear Constrained Uncertain Systems</title><title>IEEE transactions on signal processing</title><addtitle>TSP</addtitle><description>In this correspondence, a robust filter is proposed to effectively estimate the system states in the case where system model uncertainties as well as disturbances are present. 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| source | IEEE Xplore |
| subjects | Aerospace engineering Estimation error Extended robust Linear approximation Noise robustness nonlinear estimation Nonlinear filters Nonlinear systems nonlinear uncertain system robust estimation State estimation Statistics Uncertain systems Uncertainty |
| title | An Extended Robust H inftyFilter for Nonlinear Constrained Uncertain Systems |
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