Best conditioned parametric identification of transfer function models in the frequency domain
It is shown that rational transfer function models based on orthogonal Forsythe polynomials minimize the condition number of the Jacobian of estimators in a least-squares framework. As a result, very high order linear time-invariant systems can be identified. The numerical stability of the estimatio...
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| Veröffentlicht in: | IEEE transactions on automatic control 1995-11, Vol.40 (11), p.1954-1960 |
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| container_end_page | 1960 |
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| container_issue | 11 |
| container_start_page | 1954 |
| container_title | IEEE transactions on automatic control |
| container_volume | 40 |
| creator | Rolain, Y. Pintelon, R. Xu, K.Q. Vold, H. |
| description | It is shown that rational transfer function models based on orthogonal Forsythe polynomials minimize the condition number of the Jacobian of estimators in a least-squares framework. As a result, very high order linear time-invariant systems can be identified. The numerical stability of the estimation of the parameters and their derived quantities (zeros, poles, ...) are obtained. Statistical uncertainty bounds are provided. The method is illustrated on a 100th order simulated system and a 120th order measured beam-structure.< > |
| doi_str_mv | 10.1109/9.471223 |
| format | Article |
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As a result, very high order linear time-invariant systems can be identified. The numerical stability of the estimation of the parameters and their derived quantities (zeros, poles, ...) are obtained. Statistical uncertainty bounds are provided. The method is illustrated on a 100th order simulated system and a 120th order measured beam-structure.< ></description><subject>Applied sciences</subject><subject>Computer science; control theory; systems</subject><subject>Control theory. Systems</subject><subject>Cost function</subject><subject>Exact sciences and technology</subject><subject>Frequency domain analysis</subject><subject>Frequency estimation</subject><subject>Frequency measurement</subject><subject>Frequency response</subject><subject>Modelling and identification</subject><subject>Parameter estimation</subject><subject>Poles and zeros</subject><subject>Polynomials</subject><subject>Transfer functions</subject><subject>Virtual manufacturing</subject><issn>0018-9286</issn><issn>1558-2523</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1995</creationdate><recordtype>article</recordtype><recordid>eNqNkD1PwzAQhi0EEqUgMTN5QIglxR9xbI9Q8SVVYoGVyLHPwihxip0O_fekpOrMdLp7H706PQhdUrKglOg7vSglZYwfoRkVQhVMMH6MZoRQVWimqlN0lvP3uFZlSWfo8wHygG0fXRhCH8HhtUmmgyEFi4ODOAQfrNlluPd4SCZmDwn7TbR_x6530GYcIh6-APsEPxuIdotd35kQz9GJN22Gi_2co4-nx_flS7F6e35d3q8Ky7kYCgUWtDOSyEpTyZgoveLcVqCVl6AaLpwwpQbBHBBrTSPBGdsQ6aWTTcn5HN1MvevUjw_koe5CttC2JkK_yTVTiitRsX-AVMiK7sDbCbSpzzmBr9cpdCZta0rqnela15PpEb3ed5psTetHRzbkA8-EIrRUI3Y1YQEADum-4xdP24cR</recordid><startdate>19951101</startdate><enddate>19951101</enddate><creator>Rolain, Y.</creator><creator>Pintelon, R.</creator><creator>Xu, K.Q.</creator><creator>Vold, H.</creator><general>IEEE</general><general>Institute of Electrical and Electronics Engineers</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>H8D</scope></search><sort><creationdate>19951101</creationdate><title>Best conditioned parametric identification of transfer function models in the frequency domain</title><author>Rolain, Y. ; Pintelon, R. ; Xu, K.Q. ; Vold, H.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c335t-8ece9da70769172254f833c6e98f7e8b35d5a49e52de0ccab7edacb07f7d7b433</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1995</creationdate><topic>Applied sciences</topic><topic>Computer science; control theory; systems</topic><topic>Control theory. Systems</topic><topic>Cost function</topic><topic>Exact sciences and technology</topic><topic>Frequency domain analysis</topic><topic>Frequency estimation</topic><topic>Frequency measurement</topic><topic>Frequency response</topic><topic>Modelling and identification</topic><topic>Parameter estimation</topic><topic>Poles and zeros</topic><topic>Polynomials</topic><topic>Transfer functions</topic><topic>Virtual manufacturing</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Rolain, Y.</creatorcontrib><creatorcontrib>Pintelon, R.</creatorcontrib><creatorcontrib>Xu, K.Q.</creatorcontrib><creatorcontrib>Vold, H.</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering 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>Aerospace Database</collection><jtitle>IEEE transactions on automatic control</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Rolain, Y.</au><au>Pintelon, R.</au><au>Xu, K.Q.</au><au>Vold, H.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Best conditioned parametric identification of transfer function models in the frequency domain</atitle><jtitle>IEEE transactions on automatic control</jtitle><stitle>TAC</stitle><date>1995-11-01</date><risdate>1995</risdate><volume>40</volume><issue>11</issue><spage>1954</spage><epage>1960</epage><pages>1954-1960</pages><issn>0018-9286</issn><eissn>1558-2523</eissn><coden>IETAA9</coden><abstract>It is shown that rational transfer function models based on orthogonal Forsythe polynomials minimize the condition number of the Jacobian of estimators in a least-squares framework. As a result, very high order linear time-invariant systems can be identified. The numerical stability of the estimation of the parameters and their derived quantities (zeros, poles, ...) are obtained. Statistical uncertainty bounds are provided. The method is illustrated on a 100th order simulated system and a 120th order measured beam-structure.< ></abstract><cop>New York, NY</cop><pub>IEEE</pub><doi>10.1109/9.471223</doi><tpages>7</tpages></addata></record> |
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| identifier | ISSN: 0018-9286 |
| ispartof | IEEE transactions on automatic control, 1995-11, Vol.40 (11), p.1954-1960 |
| issn | 0018-9286 1558-2523 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_28838562 |
| source | IEEE Electronic Library Online |
| subjects | Applied sciences Computer science control theory systems Control theory. Systems Cost function Exact sciences and technology Frequency domain analysis Frequency estimation Frequency measurement Frequency response Modelling and identification Parameter estimation Poles and zeros Polynomials Transfer functions Virtual manufacturing |
| title | Best conditioned parametric identification of transfer function models in the frequency domain |
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