Filtering For Discrete Fuzzy Stochastic Systems With Sensor Nonlinearities
This paper deals with the filtering problem for discrete-time fuzzy stochastic systems with sensor nonlinearities. There exist time-varying parameter uncertainties and random noise depending on state and external-disturbance. The characteristic of nonlinear sensor is handled by a decomposition metho...
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| Veröffentlicht in: | IEEE transactions on fuzzy systems 2010-10, Vol.18 (5), p.971-978 |
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| container_title | IEEE transactions on fuzzy systems |
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| creator | Yugang Niu Ho, Daniel W C Li, C W |
| description | This paper deals with the filtering problem for discrete-time fuzzy stochastic systems with sensor nonlinearities. There exist time-varying parameter uncertainties and random noise depending on state and external-disturbance. The characteristic of nonlinear sensor is handled by a decomposition method. By means of the parallel distributed compensation technique, the design method of the robust H_ filter is presented. Sufficient conditions for the stochastic stability of the filtering error systems are derived such that the filter parameters can be explicitly obtained. Simulation results are given to illustrate the proposed method. |
| doi_str_mv | 10.1109/TFUZZ.2010.2060203 |
| format | Article |
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There exist time-varying parameter uncertainties and random noise depending on state and external-disturbance. The characteristic of nonlinear sensor is handled by a decomposition method. By means of the parallel distributed compensation technique, the design method of the robust H_ filter is presented. Sufficient conditions for the stochastic stability of the filtering error systems are derived such that the filter parameters can be explicitly obtained. Simulation results are given to illustrate the proposed method.</description><identifier>ISSN: 1063-6706</identifier><identifier>EISSN: 1941-0034</identifier><identifier>DOI: 10.1109/TFUZZ.2010.2060203</identifier><identifier>CODEN: IEFSEV</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Compensation ; Design methodology ; External disturbance ; Filtering ; Filters ; Filtration ; Fuzzy ; Fuzzy logic ; Fuzzy set theory ; fuzzy stochastic systems ; Fuzzy systems ; Noise robustness ; Nonlinearity ; sensor nonlinearities ; Sensor phenomena and characterization ; Sensor systems ; Sensors ; Stochastic systems ; Sufficient conditions ; Uncertain systems</subject><ispartof>IEEE transactions on fuzzy systems, 2010-10, Vol.18 (5), p.971-978</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Oct 2010</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c327t-6edf7ed1c6899f5557ec86e78e46b2adeb4925e64e8305ef4cf1e7f8f5bf087c3</citedby><cites>FETCH-LOGICAL-c327t-6edf7ed1c6899f5557ec86e78e46b2adeb4925e64e8305ef4cf1e7f8f5bf087c3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/5512637$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27903,27904,54737</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/5512637$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Yugang Niu</creatorcontrib><creatorcontrib>Ho, Daniel W C</creatorcontrib><creatorcontrib>Li, C W</creatorcontrib><title>Filtering For Discrete Fuzzy Stochastic Systems With Sensor Nonlinearities</title><title>IEEE transactions on fuzzy systems</title><addtitle>TFUZZ</addtitle><description>This paper deals with the filtering problem for discrete-time fuzzy stochastic systems with sensor nonlinearities. There exist time-varying parameter uncertainties and random noise depending on state and external-disturbance. The characteristic of nonlinear sensor is handled by a decomposition method. By means of the parallel distributed compensation technique, the design method of the robust H_ filter is presented. Sufficient conditions for the stochastic stability of the filtering error systems are derived such that the filter parameters can be explicitly obtained. Simulation results are given to illustrate the proposed method.</description><subject>Compensation</subject><subject>Design methodology</subject><subject>External disturbance</subject><subject>Filtering</subject><subject>Filters</subject><subject>Filtration</subject><subject>Fuzzy</subject><subject>Fuzzy logic</subject><subject>Fuzzy set theory</subject><subject>fuzzy stochastic systems</subject><subject>Fuzzy systems</subject><subject>Noise robustness</subject><subject>Nonlinearity</subject><subject>sensor nonlinearities</subject><subject>Sensor phenomena and characterization</subject><subject>Sensor systems</subject><subject>Sensors</subject><subject>Stochastic systems</subject><subject>Sufficient conditions</subject><subject>Uncertain systems</subject><issn>1063-6706</issn><issn>1941-0034</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2010</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpdkMtOwkAUhidGExF9Ad00ceGqOJfOpUuD1kuILoCYsGnKcEaGlBZnpgt4egchLlydc5LvP_nzIXRN8IAQnN9PiulsNqA43hQLTDE7QT2SZyTFmGWncceCpUJicY4uvF9hTDJOVA-9FbYO4GzzlRStSx6t1w4CJEW3222TcWj1svLB6mS89QHWPvm0YZmMofGRfm-b2jZQORss-Et0Zqraw9Vx9tG0eJoMX9LRx_Pr8GGUakZlSAUsjIQF0ULlueGcS9BKgFSQiTmtFjDPcspBZKAY5mAybQhIowyfG6ykZn10d_i7ce13Bz6U69ga6rpqoO18qRghXImcR_L2H7lqO9fEciXBDBOqqKSRogdKu9Z7B6bcOLuu3DZC5d5u-Wu33Nstj3Zj6OYQsgDwF-CcUMEk-wHrV3a4</recordid><startdate>201010</startdate><enddate>201010</enddate><creator>Yugang Niu</creator><creator>Ho, Daniel W C</creator><creator>Li, C W</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>7SP</scope><scope>F28</scope><scope>FR3</scope></search><sort><creationdate>201010</creationdate><title>Filtering For Discrete Fuzzy Stochastic Systems With Sensor Nonlinearities</title><author>Yugang Niu ; Ho, Daniel W C ; Li, C W</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c327t-6edf7ed1c6899f5557ec86e78e46b2adeb4925e64e8305ef4cf1e7f8f5bf087c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Compensation</topic><topic>Design methodology</topic><topic>External disturbance</topic><topic>Filtering</topic><topic>Filters</topic><topic>Filtration</topic><topic>Fuzzy</topic><topic>Fuzzy logic</topic><topic>Fuzzy set theory</topic><topic>fuzzy stochastic systems</topic><topic>Fuzzy systems</topic><topic>Noise robustness</topic><topic>Nonlinearity</topic><topic>sensor nonlinearities</topic><topic>Sensor phenomena and characterization</topic><topic>Sensor systems</topic><topic>Sensors</topic><topic>Stochastic systems</topic><topic>Sufficient conditions</topic><topic>Uncertain systems</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Yugang Niu</creatorcontrib><creatorcontrib>Ho, Daniel W C</creatorcontrib><creatorcontrib>Li, C W</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005–Present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998–Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Electronics & Communications Abstracts</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><jtitle>IEEE transactions on fuzzy systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Yugang Niu</au><au>Ho, Daniel W C</au><au>Li, C W</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Filtering For Discrete Fuzzy Stochastic Systems With Sensor Nonlinearities</atitle><jtitle>IEEE transactions on fuzzy systems</jtitle><stitle>TFUZZ</stitle><date>2010-10</date><risdate>2010</risdate><volume>18</volume><issue>5</issue><spage>971</spage><epage>978</epage><pages>971-978</pages><issn>1063-6706</issn><eissn>1941-0034</eissn><coden>IEFSEV</coden><abstract>This paper deals with the filtering problem for discrete-time fuzzy stochastic systems with sensor nonlinearities. 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| ispartof | IEEE transactions on fuzzy systems, 2010-10, Vol.18 (5), p.971-978 |
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| language | eng |
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| source | IEEE Electronic Library (IEL) |
| subjects | Compensation Design methodology External disturbance Filtering Filters Filtration Fuzzy Fuzzy logic Fuzzy set theory fuzzy stochastic systems Fuzzy systems Noise robustness Nonlinearity sensor nonlinearities Sensor phenomena and characterization Sensor systems Sensors Stochastic systems Sufficient conditions Uncertain systems |
| title | Filtering For Discrete Fuzzy Stochastic Systems With Sensor Nonlinearities |
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