Sampling in Parametric and Nonparametric System Identification: Aliasing, Input Conditions, and Consistency
The sampling rate of input and output signals is known to play a critical role in the identification and control of dynamical systems. For slow-sampled continuous-time systems that do not satisfy the Nyquist-Shannon sampling condition for perfect signal reconstructability, careful consideration is r...
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| Veröffentlicht in: | IEEE control systems letters 2024, Vol.8, p.2415-2420 |
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| container_title | IEEE control systems letters |
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| creator | Gonzalez, Rodrigo A. van Haren, Max Oomen, Tom Rojas, Cristian R. |
| description | The sampling rate of input and output signals is known to play a critical role in the identification and control of dynamical systems. For slow-sampled continuous-time systems that do not satisfy the Nyquist-Shannon sampling condition for perfect signal reconstructability, careful consideration is required when identifying parametric and nonparametric models. In this letter, a comprehensive statistical analysis of estimators under slow sampling is performed. Necessary and sufficient conditions are obtained for unbiased estimates of the frequency response function beyond the Nyquist frequency, and it is shown that consistency of parametric estimators can be achieved even if input frequencies overlap after aliasing. Monte Carlo simulations confirm the theoretical properties. |
| doi_str_mv | 10.1109/LCSYS.2024.3487501 |
| format | Article |
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Monte Carlo simulations confirm the theoretical properties.</description><subject>Frequency estimation</subject><subject>Frequency response</subject><subject>frequency response function</subject><subject>Frequency-domain analysis</subject><subject>Frequency-domain system identification</subject><subject>Matrix decomposition</subject><subject>Polynomials</subject><subject>Sufficient conditions</subject><subject>System identification</subject><subject>Time-domain analysis</subject><subject>undersampled systems</subject><subject>Vectors</subject><subject>White noise</subject><issn>2475-1456</issn><issn>2475-1456</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpNkLtOwzAUhi0EElXpCyAGP0BTfBxfYrYq4lKpAqTAwBQ57gkyNE4Uh6FvT1oq0elcv3_4CLkGtgBg5nadFx_FgjMuFqnItGRwRiZcaJmAkOr8pL8ksxi_GGOQcc24mZDvwjbd1odP6gN9tb1tcOi9ozZs6HMbuv9NsYsDNnS1wTD42js7-Dbc0eXW2zjyc7oK3c9A8zZs_P4U54eQcY5-JIPbXZGL2m4jzo51St4f7t_yp2T98rjKl-vEgTBDglIKQAc1N1wJqdG5NGVgnTGuEhXnJmMiGx8yi7WrMlQOq1oppcFJiSydEv6X6_o2xh7rsut9Y_tdCazcGysPxsq9sfJobIRu_iCPiCeATjVwlf4C1Mhpvg</recordid><startdate>2024</startdate><enddate>2024</enddate><creator>Gonzalez, Rodrigo A.</creator><creator>van Haren, Max</creator><creator>Oomen, Tom</creator><creator>Rojas, Cristian R.</creator><general>IEEE</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><orcidid>https://orcid.org/0000-0003-0355-2663</orcidid><orcidid>https://orcid.org/0000-0003-1243-1871</orcidid><orcidid>https://orcid.org/0000-0001-7721-4566</orcidid><orcidid>https://orcid.org/0000-0002-5106-2784</orcidid></search><sort><creationdate>2024</creationdate><title>Sampling in Parametric and Nonparametric System Identification: Aliasing, Input Conditions, and Consistency</title><author>Gonzalez, Rodrigo A. ; van Haren, Max ; Oomen, Tom ; Rojas, Cristian R.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c149t-e5541ec1f2926457ecc3301ac99cb4b2298048ec18aefcb8e6cebf66671c55e03</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Frequency estimation</topic><topic>Frequency response</topic><topic>frequency response function</topic><topic>Frequency-domain analysis</topic><topic>Frequency-domain system identification</topic><topic>Matrix decomposition</topic><topic>Polynomials</topic><topic>Sufficient conditions</topic><topic>System identification</topic><topic>Time-domain analysis</topic><topic>undersampled systems</topic><topic>Vectors</topic><topic>White noise</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Gonzalez, Rodrigo A.</creatorcontrib><creatorcontrib>van Haren, Max</creatorcontrib><creatorcontrib>Oomen, Tom</creatorcontrib><creatorcontrib>Rojas, Cristian R.</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998–Present</collection><collection>IEEE/IET Electronic Library</collection><collection>CrossRef</collection><jtitle>IEEE control systems letters</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Gonzalez, Rodrigo A.</au><au>van Haren, Max</au><au>Oomen, Tom</au><au>Rojas, Cristian R.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Sampling in Parametric and Nonparametric System Identification: Aliasing, Input Conditions, and Consistency</atitle><jtitle>IEEE control systems letters</jtitle><stitle>LCSYS</stitle><date>2024</date><risdate>2024</risdate><volume>8</volume><spage>2415</spage><epage>2420</epage><pages>2415-2420</pages><issn>2475-1456</issn><eissn>2475-1456</eissn><coden>ICSLBO</coden><abstract>The sampling rate of input and output signals is known to play a critical role in the identification and control of dynamical systems. 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| subjects | Frequency estimation Frequency response frequency response function Frequency-domain analysis Frequency-domain system identification Matrix decomposition Polynomials Sufficient conditions System identification Time-domain analysis undersampled systems Vectors White noise |
| title | Sampling in Parametric and Nonparametric System Identification: Aliasing, Input Conditions, and Consistency |
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