Identification of state-space models by modified nonlinear ls optimization method
The problem of estimating parameter of LTI state-space system is addressed in this paper. A modified nonlinear least square(NNLS) method is proposed to the optimization of output error cost function. The nonuniqueness of the fully parameterized state-space is considered and the parameter update is r...
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| creator | Lusheng Zhong Hui Yang Rongxiu Lu Sun Baohua Meng Shasha |
| description | The problem of estimating parameter of LTI state-space system is addressed in this paper. A modified nonlinear least square(NNLS) method is proposed to the optimization of output error cost function. The nonuniqueness of the fully parameterized state-space is considered and the parameter update is restricted to the directions that change the input-output behavior of the system. Simulation studies show the improved performance of the proposed method. |
| doi_str_mv | 10.1109/CCDC.2009.5192350 |
| format | Conference Proceeding |
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A modified nonlinear least square(NNLS) method is proposed to the optimization of output error cost function. The nonuniqueness of the fully parameterized state-space is considered and the parameter update is restricted to the directions that change the input-output behavior of the system. 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Simulation studies show the improved performance of the proposed method.</description><subject>Cost function</subject><subject>Educational institutions</subject><subject>Gaussian distribution</subject><subject>Gaussian noise</subject><subject>Nonlinear Least Square</subject><subject>Optimization methods</subject><subject>Parameter estimation</subject><subject>Space technology</subject><subject>State estimation</subject><subject>State-Space Model</subject><subject>Sun</subject><subject>System identification</subject><issn>1948-9439</issn><issn>1948-9447</issn><isbn>9781424427222</isbn><isbn>1424427223</isbn><isbn>9781424427239</isbn><isbn>1424427231</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2009</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNpVkEtrwzAQhNVHoGmaH1B68R9wuqtHrD0W9xUIlELuQZZWVCW2Q6xL-uvr0lDoXHbgm53DCHGLsEAEuq_rx3ohAWhhkKQycCbmVFnUUmtZSUXnYoqkbUlaVxf_mJSXf0zRRFyPNZZgCbi8EvNh-IRR2iijcCreV4G7nGLyLqe-K_pYDNllLoe981y0feDdUDTHHzemOBRd3-1Sx-5QjKDf59Smr9_flvNHH27EJLrdwPPTnYnN89Omfi3Xby-r-mFdJoJcaq60VA1aQKujapxD8DpIb8H6KiJEZpZLVoBMSlPVUDAuBG8Me4hWzcTdb20ag9v9IbXucNyexlLfuHNXtQ</recordid><startdate>200906</startdate><enddate>200906</enddate><creator>Lusheng Zhong</creator><creator>Hui Yang</creator><creator>Rongxiu Lu</creator><creator>Sun Baohua</creator><creator>Meng Shasha</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>200906</creationdate><title>Identification of state-space models by modified nonlinear ls optimization method</title><author>Lusheng Zhong ; Hui Yang ; Rongxiu Lu ; Sun Baohua ; Meng Shasha</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-4e7423b180184f3baa10c4d2c808c7f10feee26e301e93497b9d5addc55ec0f83</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2009</creationdate><topic>Cost function</topic><topic>Educational institutions</topic><topic>Gaussian distribution</topic><topic>Gaussian noise</topic><topic>Nonlinear Least Square</topic><topic>Optimization methods</topic><topic>Parameter estimation</topic><topic>Space technology</topic><topic>State estimation</topic><topic>State-Space Model</topic><topic>Sun</topic><topic>System identification</topic><toplevel>online_resources</toplevel><creatorcontrib>Lusheng Zhong</creatorcontrib><creatorcontrib>Hui Yang</creatorcontrib><creatorcontrib>Rongxiu Lu</creatorcontrib><creatorcontrib>Sun Baohua</creatorcontrib><creatorcontrib>Meng Shasha</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Lusheng Zhong</au><au>Hui Yang</au><au>Rongxiu Lu</au><au>Sun Baohua</au><au>Meng Shasha</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Identification of state-space models by modified nonlinear ls optimization method</atitle><btitle>2009 Chinese Control and Decision Conference</btitle><stitle>CCDC</stitle><date>2009-06</date><risdate>2009</risdate><spage>1184</spage><epage>1187</epage><pages>1184-1187</pages><issn>1948-9439</issn><eissn>1948-9447</eissn><isbn>9781424427222</isbn><isbn>1424427223</isbn><eisbn>9781424427239</eisbn><eisbn>1424427231</eisbn><abstract>The problem of estimating parameter of LTI state-space system is addressed in this paper. A modified nonlinear least square(NNLS) method is proposed to the optimization of output error cost function. The nonuniqueness of the fully parameterized state-space is considered and the parameter update is restricted to the directions that change the input-output behavior of the system. Simulation studies show the improved performance of the proposed method.</abstract><pub>IEEE</pub><doi>10.1109/CCDC.2009.5192350</doi><tpages>4</tpages></addata></record> |
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| identifier | ISSN: 1948-9439 |
| ispartof | 2009 Chinese Control and Decision Conference, 2009, p.1184-1187 |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Cost function Educational institutions Gaussian distribution Gaussian noise Nonlinear Least Square Optimization methods Parameter estimation Space technology State estimation State-Space Model Sun System identification |
| title | Identification of state-space models by modified nonlinear ls optimization method |
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