A research about a MIMO system identification algorithm based on ANN using slide mode variable structure
Applying sliding mode variable structure control to train neural networks is proposed in this paper, which can not only increases learning rate but also improves the stability of neural-network. Furthermore, this method helps to promote the generalization capacity of neural-network. In order to impr...
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| creator | Yahui Wang Peixin Cheng Zhifeng Xia |
| description | Applying sliding mode variable structure control to train neural networks is proposed in this paper, which can not only increases learning rate but also improves the stability of neural-network. Furthermore, this method helps to promote the generalization capacity of neural-network. In order to improve the generalization ability, two sliding mode objective functions are designed based on previous researches for a new neural-network learning algorithm. Simulation analysis shows that the proposed algorithm increases the generalization ability and robustness of neural-network, meanwhile, enhances the identification accuracy. |
| doi_str_mv | 10.1109/CCDC.2011.5968817 |
| format | Conference Proceeding |
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Simulation analysis shows that the proposed algorithm increases the generalization ability and robustness of neural-network, meanwhile, enhances the identification accuracy.</description><subject>Algorithm design and analysis</subject><subject>Artificial neural networks</subject><subject>Generalization Ability</subject><subject>Least squares approximation</subject><subject>MIMO System Identification</subject><subject>Neural-Network</subject><subject>Robustness</subject><subject>Sliding mode control</subject><subject>Sliding Mode Variable Structure</subject><subject>Training</subject><subject>Training data</subject><issn>1948-9439</issn><issn>1948-9447</issn><isbn>9781424487370</isbn><isbn>1424487374</isbn><isbn>9781424487363</isbn><isbn>1424487382</isbn><isbn>9781424487387</isbn><isbn>1424487366</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2011</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNpVUMlqwzAUVDdoSPMBpRf9gFPJ2o_B3QJZLrkHWXpOVOy4SHIhf19DQ6FzmAczw_AYhB4pmVNKzHNVvVTzklA6F0ZqTdUVmhmlKS8514pJdo0m1HBdGM7VzT9Pkds_j5l7NEvpk4yQ0pDSTNBxgSMksNEdsa37IWOL18v1FqdzytDh4OGUQxOczaE_Ydse-hjyscO1TeDxKC02GzykcDrg1I5p3PUjfdsYbN0CTjkOLg8RHtBdY9sEs8udot3b6676KFbb92W1WBWBKpELIM34M2dUgyhN7YXghAsAC8qVjClLjOeuJtY4Sr3k2jOuneOSSV8KYFP09FsbAGD_FUNn43l_mY39AFG5XG4</recordid><startdate>201105</startdate><enddate>201105</enddate><creator>Yahui Wang</creator><creator>Peixin Cheng</creator><creator>Zhifeng Xia</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201105</creationdate><title>A research about a MIMO system identification algorithm based on ANN using slide mode variable structure</title><author>Yahui Wang ; Peixin Cheng ; Zhifeng Xia</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-e0f3704318e529bd554045eeae7c2337a09d4cb0a9c11d648d348cc4636d25e3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Algorithm design and analysis</topic><topic>Artificial neural networks</topic><topic>Generalization Ability</topic><topic>Least squares approximation</topic><topic>MIMO System Identification</topic><topic>Neural-Network</topic><topic>Robustness</topic><topic>Sliding mode control</topic><topic>Sliding Mode Variable Structure</topic><topic>Training</topic><topic>Training data</topic><toplevel>online_resources</toplevel><creatorcontrib>Yahui Wang</creatorcontrib><creatorcontrib>Peixin Cheng</creatorcontrib><creatorcontrib>Zhifeng Xia</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 Xplore</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>Yahui Wang</au><au>Peixin Cheng</au><au>Zhifeng Xia</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>A research about a MIMO system identification algorithm based on ANN using slide mode variable structure</atitle><btitle>2011 Chinese Control and Decision Conference (CCDC)</btitle><stitle>CCDC</stitle><date>2011-05</date><risdate>2011</risdate><spage>3248</spage><epage>3253</epage><pages>3248-3253</pages><issn>1948-9439</issn><eissn>1948-9447</eissn><isbn>9781424487370</isbn><isbn>1424487374</isbn><eisbn>9781424487363</eisbn><eisbn>1424487382</eisbn><eisbn>9781424487387</eisbn><eisbn>1424487366</eisbn><abstract>Applying sliding mode variable structure control to train neural networks is proposed in this paper, which can not only increases learning rate but also improves the stability of neural-network. Furthermore, this method helps to promote the generalization capacity of neural-network. In order to improve the generalization ability, two sliding mode objective functions are designed based on previous researches for a new neural-network learning algorithm. Simulation analysis shows that the proposed algorithm increases the generalization ability and robustness of neural-network, meanwhile, enhances the identification accuracy.</abstract><pub>IEEE</pub><doi>10.1109/CCDC.2011.5968817</doi><tpages>6</tpages></addata></record> |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Algorithm design and analysis Artificial neural networks Generalization Ability Least squares approximation MIMO System Identification Neural-Network Robustness Sliding mode control Sliding Mode Variable Structure Training Training data |
| title | A research about a MIMO system identification algorithm based on ANN using slide mode variable structure |
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