Cone Crusher Model Identification Using Block-Oriented Systems with Orthonormal Basis Functions
In this paper, block-oriented systems with linear parts based on Laguerre functions is used to approximation of a cone crusher dynamics. Adaptive recursive least squares algorithm is used to identification of Laguerre model. Various structures of Hammerstein, Wiener, Hammerstein-Wiener models are te...
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| creator | Mykhailenko, Oleksii |
| description | In this paper, block-oriented systems with linear parts based on Laguerre
functions is used to approximation of a cone crusher dynamics. Adaptive
recursive least squares algorithm is used to identification of Laguerre model.
Various structures of Hammerstein, Wiener, Hammerstein-Wiener models are tested
and the MATLAB simulation results are compared. The mean square error is used
for models validation. It has been found that Hammerstein-Wiener with
orthonormal basis functions improves the quality of approximation plant
dynamics. The mean square error for this model is 11% on average throughout the
considered range of the external disturbances amplitude. The analysis also
showed that Wiener model cannot provide sufficient approximation accuracy of
the cone crusher dynamics. During the process it is unstable due to the high
sensitivity to disturbances on the output. The Hammerstein-Wiener model will be
used to the design nonlinear model predictive control application. |
| doi_str_mv | 10.48550/arxiv.1408.3929 |
| format | Article |
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functions is used to approximation of a cone crusher dynamics. Adaptive
recursive least squares algorithm is used to identification of Laguerre model.
Various structures of Hammerstein, Wiener, Hammerstein-Wiener models are tested
and the MATLAB simulation results are compared. The mean square error is used
for models validation. It has been found that Hammerstein-Wiener with
orthonormal basis functions improves the quality of approximation plant
dynamics. The mean square error for this model is 11% on average throughout the
considered range of the external disturbances amplitude. The analysis also
showed that Wiener model cannot provide sufficient approximation accuracy of
the cone crusher dynamics. During the process it is unstable due to the high
sensitivity to disturbances on the output. The Hammerstein-Wiener model will be
used to the design nonlinear model predictive control application.</description><identifier>DOI: 10.48550/arxiv.1408.3929</identifier><language>eng</language><subject>Computer Science - Systems and Control</subject><creationdate>2014-08</creationdate><rights>http://arxiv.org/licenses/nonexclusive-distrib/1.0</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,780,885</link.rule.ids><linktorsrc>$$Uhttps://arxiv.org/abs/1408.3929$$EView_record_in_Cornell_University$$FView_record_in_$$GCornell_University$$Hfree_for_read</linktorsrc><backlink>$$Uhttps://doi.org/10.48550/arXiv.1408.3929$$DView paper in arXiv$$Hfree_for_read</backlink></links><search><creatorcontrib>Mykhailenko, Oleksii</creatorcontrib><title>Cone Crusher Model Identification Using Block-Oriented Systems with Orthonormal Basis Functions</title><description>In this paper, block-oriented systems with linear parts based on Laguerre
functions is used to approximation of a cone crusher dynamics. Adaptive
recursive least squares algorithm is used to identification of Laguerre model.
Various structures of Hammerstein, Wiener, Hammerstein-Wiener models are tested
and the MATLAB simulation results are compared. The mean square error is used
for models validation. It has been found that Hammerstein-Wiener with
orthonormal basis functions improves the quality of approximation plant
dynamics. The mean square error for this model is 11% on average throughout the
considered range of the external disturbances amplitude. The analysis also
showed that Wiener model cannot provide sufficient approximation accuracy of
the cone crusher dynamics. During the process it is unstable due to the high
sensitivity to disturbances on the output. The Hammerstein-Wiener model will be
used to the design nonlinear model predictive control application.</description><subject>Computer Science - Systems and Control</subject><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><sourceid>GOX</sourceid><recordid>eNotz7tOwzAYBWAvDKiwMyG_QILjS2OPNKJQqVUGyhz98YVYJDayU6BvDwGmMxydI30I3VSk5FIIcgfpy3-UFSeyZIqqS9Q1MVjcpFMebMKHaOyId8aG2TuvYfYx4JfswyvejFG_FW3yP501-PmcZztl_OnnAbdpHmKIaYIRbyD7jLenoJdxvkIXDsZsr_9zhY7bh2PzVOzbx11zvy9gLVTBec2tI1KvRV8rrR2vLaMgiewNVZZzZoQVtIK6koxQ4LTnhvbOGam5A8VW6Pbv9hfYvSc_QTp3C7RboOwbOBxPTg</recordid><startdate>20140818</startdate><enddate>20140818</enddate><creator>Mykhailenko, Oleksii</creator><scope>AKY</scope><scope>GOX</scope></search><sort><creationdate>20140818</creationdate><title>Cone Crusher Model Identification Using Block-Oriented Systems with Orthonormal Basis Functions</title><author>Mykhailenko, Oleksii</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a659-4474ef08c65b79ccf47e32a808bd29e443d5e521a718302a42b4d2bffd8c4fa93</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Computer Science - Systems and Control</topic><toplevel>online_resources</toplevel><creatorcontrib>Mykhailenko, Oleksii</creatorcontrib><collection>arXiv Computer Science</collection><collection>arXiv.org</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Mykhailenko, Oleksii</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Cone Crusher Model Identification Using Block-Oriented Systems with Orthonormal Basis Functions</atitle><date>2014-08-18</date><risdate>2014</risdate><abstract>In this paper, block-oriented systems with linear parts based on Laguerre
functions is used to approximation of a cone crusher dynamics. Adaptive
recursive least squares algorithm is used to identification of Laguerre model.
Various structures of Hammerstein, Wiener, Hammerstein-Wiener models are tested
and the MATLAB simulation results are compared. The mean square error is used
for models validation. It has been found that Hammerstein-Wiener with
orthonormal basis functions improves the quality of approximation plant
dynamics. The mean square error for this model is 11% on average throughout the
considered range of the external disturbances amplitude. The analysis also
showed that Wiener model cannot provide sufficient approximation accuracy of
the cone crusher dynamics. During the process it is unstable due to the high
sensitivity to disturbances on the output. The Hammerstein-Wiener model will be
used to the design nonlinear model predictive control application.</abstract><doi>10.48550/arxiv.1408.3929</doi><oa>free_for_read</oa></addata></record> |
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| subjects | Computer Science - Systems and Control |
| title | Cone Crusher Model Identification Using Block-Oriented Systems with Orthonormal Basis Functions |
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