Control method of brushless direct current motor based on neural network feedforward compensation
The invention discloses a control method for a brushless direct current motor based on neural network feedforward compensation. The control method comprises the following steps of taking the brushless direct current motor as a second-order nonlinear system; calculating a position error according to...
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| creator | SUN ZHAOLONG ZHOU WEICHANG ZHUANG ZHEXIN MAO YINHAO HUANG CHUIBING LIU ZHENTIAN QIAN HANNING DING ANMIN ZHENG WEI |
| description | The invention discloses a control method for a brushless direct current motor based on neural network feedforward compensation. The control method comprises the following steps of taking the brushless direct current motor as a second-order nonlinear system; calculating a position error according to the difference between the expectation of the control object and the current rotating speed or current of the motor; an equation of a closed-loop control system being obtained by designing an input u of the system as a PD control rate based on feed-forward and compensation; establishing a three-layer radial basis function neural network, and performing approximation on an expression of disturbance of environmental factors to the motor by using the three-layer radial basis function neural network; the output of the RBF neural network being used as the disturbance compensation of the brushless direct current motor; the input of the system being designed to be a PD adaptive control law of a brushless direct current mo |
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The control method comprises the following steps of taking the brushless direct current motor as a second-order nonlinear system; calculating a position error according to the difference between the expectation of the control object and the current rotating speed or current of the motor; an equation of a closed-loop control system being obtained by designing an input u of the system as a PD control rate based on feed-forward and compensation; establishing a three-layer radial basis function neural network, and performing approximation on an expression of disturbance of environmental factors to the motor by using the three-layer radial basis function neural network; the output of the RBF neural network being used as the disturbance compensation of the brushless direct current motor; the input of the system being designed to be a PD adaptive control law of a brushless direct current mo</description><language>chi ; eng</language><subject>CONTROL OR REGULATING SYSTEMS IN GENERAL ; CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORSOR DYNAMO-ELECTRIC CONVERTERS ; CONTROLLING ; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS ; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER ; ELECTRICITY ; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS ; GENERATION ; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS ORELEMENTS ; PHYSICS ; REGULATING</subject><creationdate>2021</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20211105&DB=EPODOC&CC=CN&NR=113612418A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,776,881,25542,76290</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20211105&DB=EPODOC&CC=CN&NR=113612418A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>SUN ZHAOLONG</creatorcontrib><creatorcontrib>ZHOU WEICHANG</creatorcontrib><creatorcontrib>ZHUANG ZHEXIN</creatorcontrib><creatorcontrib>MAO YINHAO</creatorcontrib><creatorcontrib>HUANG CHUIBING</creatorcontrib><creatorcontrib>LIU ZHENTIAN</creatorcontrib><creatorcontrib>QIAN HANNING</creatorcontrib><creatorcontrib>DING ANMIN</creatorcontrib><creatorcontrib>ZHENG WEI</creatorcontrib><title>Control method of brushless direct current motor based on neural network feedforward compensation</title><description>The invention discloses a control method for a brushless direct current motor based on neural network feedforward compensation. The control method comprises the following steps of taking the brushless direct current motor as a second-order nonlinear system; calculating a position error according to the difference between the expectation of the control object and the current rotating speed or current of the motor; an equation of a closed-loop control system being obtained by designing an input u of the system as a PD control rate based on feed-forward and compensation; establishing a three-layer radial basis function neural network, and performing approximation on an expression of disturbance of environmental factors to the motor by using the three-layer radial basis function neural network; the output of the RBF neural network being used as the disturbance compensation of the brushless direct current motor; the input of the system being designed to be a PD adaptive control law of a brushless direct current mo</description><subject>CONTROL OR REGULATING SYSTEMS IN GENERAL</subject><subject>CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORSOR DYNAMO-ELECTRIC CONVERTERS</subject><subject>CONTROLLING</subject><subject>CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS</subject><subject>CONVERSION OR DISTRIBUTION OF ELECTRIC POWER</subject><subject>ELECTRICITY</subject><subject>FUNCTIONAL ELEMENTS OF SUCH SYSTEMS</subject><subject>GENERATION</subject><subject>MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS ORELEMENTS</subject><subject>PHYSICS</subject><subject>REGULATING</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2021</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNzDEOwjAMQNEuDAi4gzkAQyhCrCgCMTGxV27iqFXTuLJd9fp04ABMf3n62wo9FxPOMJJ1HIETtDJrl0kVYi8UDMIsQsVgZGOBFpVWV6DQLJjX2MIyQCKKiWVBiRB4nKgoWs9lX20SZqXDr7vq-Hx8_OtEEzekEwZaF41_O1df3fnibvf6H_MFcHY-hQ</recordid><startdate>20211105</startdate><enddate>20211105</enddate><creator>SUN ZHAOLONG</creator><creator>ZHOU WEICHANG</creator><creator>ZHUANG ZHEXIN</creator><creator>MAO YINHAO</creator><creator>HUANG CHUIBING</creator><creator>LIU ZHENTIAN</creator><creator>QIAN HANNING</creator><creator>DING ANMIN</creator><creator>ZHENG WEI</creator><scope>EVB</scope></search><sort><creationdate>20211105</creationdate><title>Control method of brushless direct current motor based on neural network feedforward compensation</title><author>SUN ZHAOLONG ; ZHOU WEICHANG ; ZHUANG ZHEXIN ; MAO YINHAO ; HUANG CHUIBING ; LIU ZHENTIAN ; QIAN HANNING ; DING ANMIN ; ZHENG WEI</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN113612418A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2021</creationdate><topic>CONTROL OR REGULATING SYSTEMS IN GENERAL</topic><topic>CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORSOR DYNAMO-ELECTRIC CONVERTERS</topic><topic>CONTROLLING</topic><topic>CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS</topic><topic>CONVERSION OR DISTRIBUTION OF ELECTRIC POWER</topic><topic>ELECTRICITY</topic><topic>FUNCTIONAL ELEMENTS OF SUCH SYSTEMS</topic><topic>GENERATION</topic><topic>MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS ORELEMENTS</topic><topic>PHYSICS</topic><topic>REGULATING</topic><toplevel>online_resources</toplevel><creatorcontrib>SUN ZHAOLONG</creatorcontrib><creatorcontrib>ZHOU WEICHANG</creatorcontrib><creatorcontrib>ZHUANG ZHEXIN</creatorcontrib><creatorcontrib>MAO YINHAO</creatorcontrib><creatorcontrib>HUANG CHUIBING</creatorcontrib><creatorcontrib>LIU ZHENTIAN</creatorcontrib><creatorcontrib>QIAN HANNING</creatorcontrib><creatorcontrib>DING ANMIN</creatorcontrib><creatorcontrib>ZHENG WEI</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>SUN ZHAOLONG</au><au>ZHOU WEICHANG</au><au>ZHUANG ZHEXIN</au><au>MAO YINHAO</au><au>HUANG CHUIBING</au><au>LIU ZHENTIAN</au><au>QIAN HANNING</au><au>DING ANMIN</au><au>ZHENG WEI</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Control method of brushless direct current motor based on neural network feedforward compensation</title><date>2021-11-05</date><risdate>2021</risdate><abstract>The invention discloses a control method for a brushless direct current motor based on neural network feedforward compensation. The control method comprises the following steps of taking the brushless direct current motor as a second-order nonlinear system; calculating a position error according to the difference between the expectation of the control object and the current rotating speed or current of the motor; an equation of a closed-loop control system being obtained by designing an input u of the system as a PD control rate based on feed-forward and compensation; establishing a three-layer radial basis function neural network, and performing approximation on an expression of disturbance of environmental factors to the motor by using the three-layer radial basis function neural network; the output of the RBF neural network being used as the disturbance compensation of the brushless direct current motor; the input of the system being designed to be a PD adaptive control law of a brushless direct current mo</abstract><oa>free_for_read</oa></addata></record> |
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| subjects | CONTROL OR REGULATING SYSTEMS IN GENERAL CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORSOR DYNAMO-ELECTRIC CONVERTERS CONTROLLING CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS CONVERSION OR DISTRIBUTION OF ELECTRIC POWER ELECTRICITY FUNCTIONAL ELEMENTS OF SUCH SYSTEMS GENERATION MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS ORELEMENTS PHYSICS REGULATING |
| title | Control method of brushless direct current motor based on neural network feedforward compensation |
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