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Model Predictive MRAS Estimator for Sensorless Induction Motor Drives
This paper presents a novel predictive model reference adaptive system (MRAS) speed estimator for sensorless induction motor (IM) drives applications. The proposed estimator is based on the finite control set-model predictive control (FCS-MPC) principle. The rotor position is calculated using a sear...
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Published in: | IEEE transactions on industrial electronics (1982) 2016-06, Vol.63 (6), p.3511-3521 |
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container_title | IEEE transactions on industrial electronics (1982) |
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creator | Zbede, Yaman B. Gadoue, Shady M. Atkinson, David J. |
description | This paper presents a novel predictive model reference adaptive system (MRAS) speed estimator for sensorless induction motor (IM) drives applications. The proposed estimator is based on the finite control set-model predictive control (FCS-MPC) principle. The rotor position is calculated using a search-based optimization algorithm which ensures a minimum speed tuning error signal at each sampling period. This eliminates the need for a proportional-integral (PI) controller which is conventionally employed in the adaption mechanism of MRAS estimators. Extensive experimental tests have been carried out to evaluate the performance of the proposed estimator using a 2.2-kW IM with a field-oriented control (FOC) scheme employed as the motor control strategy. Experimental results show improved performance of the MRAS scheme in both open- and closed-loop sensorless modes of operation at low speeds and with different loading conditions including regeneration. The proposed scheme also improves the system robustness against motor parameter variations and increases the maximum bandwidth of the speed loop controller. |
doi_str_mv | 10.1109/TIE.2016.2521721 |
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The proposed estimator is based on the finite control set-model predictive control (FCS-MPC) principle. The rotor position is calculated using a search-based optimization algorithm which ensures a minimum speed tuning error signal at each sampling period. This eliminates the need for a proportional-integral (PI) controller which is conventionally employed in the adaption mechanism of MRAS estimators. Extensive experimental tests have been carried out to evaluate the performance of the proposed estimator using a 2.2-kW IM with a field-oriented control (FOC) scheme employed as the motor control strategy. Experimental results show improved performance of the MRAS scheme in both open- and closed-loop sensorless modes of operation at low speeds and with different loading conditions including regeneration. The proposed scheme also improves the system robustness against motor parameter variations and increases the maximum bandwidth of the speed loop controller.</description><identifier>ISSN: 0278-0046</identifier><identifier>EISSN: 1557-9948</identifier><identifier>DOI: 10.1109/TIE.2016.2521721</identifier><identifier>CODEN: ITIED6</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Adaptation models ; Cost function ; induction motor drive ; Inverters ; Mathematical model ; Model reference adaptive control ; Motors ; Performance evaluation ; position estimation ; Predictive control ; Rotors ; speed estimation ; Stators ; vector control</subject><ispartof>IEEE transactions on industrial electronics (1982), 2016-06, Vol.63 (6), p.3511-3521</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2016</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c333t-9e7fe6aea8143c4e89989eab155d6761915ce852627c6de475ae3ee86cda34ce3</citedby><cites>FETCH-LOGICAL-c333t-9e7fe6aea8143c4e89989eab155d6761915ce852627c6de475ae3ee86cda34ce3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/7393559$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>315,786,790,27957,27958,55147</link.rule.ids></links><search><creatorcontrib>Zbede, Yaman B.</creatorcontrib><creatorcontrib>Gadoue, Shady M.</creatorcontrib><creatorcontrib>Atkinson, David J.</creatorcontrib><title>Model Predictive MRAS Estimator for Sensorless Induction Motor Drives</title><title>IEEE transactions on industrial electronics (1982)</title><addtitle>TIE</addtitle><description>This paper presents a novel predictive model reference adaptive system (MRAS) speed estimator for sensorless induction motor (IM) drives applications. The proposed estimator is based on the finite control set-model predictive control (FCS-MPC) principle. The rotor position is calculated using a search-based optimization algorithm which ensures a minimum speed tuning error signal at each sampling period. This eliminates the need for a proportional-integral (PI) controller which is conventionally employed in the adaption mechanism of MRAS estimators. Extensive experimental tests have been carried out to evaluate the performance of the proposed estimator using a 2.2-kW IM with a field-oriented control (FOC) scheme employed as the motor control strategy. Experimental results show improved performance of the MRAS scheme in both open- and closed-loop sensorless modes of operation at low speeds and with different loading conditions including regeneration. The proposed scheme also improves the system robustness against motor parameter variations and increases the maximum bandwidth of the speed loop controller.</description><subject>Adaptation models</subject><subject>Cost function</subject><subject>induction motor drive</subject><subject>Inverters</subject><subject>Mathematical model</subject><subject>Model reference adaptive control</subject><subject>Motors</subject><subject>Performance evaluation</subject><subject>position estimation</subject><subject>Predictive control</subject><subject>Rotors</subject><subject>speed estimation</subject><subject>Stators</subject><subject>vector control</subject><issn>0278-0046</issn><issn>1557-9948</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><recordid>eNo9kEtLAzEURoMoWKt7wc2A66m5eWdZ6qiFFsXWdRgzd2BKndRkKvjvTWlxEe4i57uPQ8gt0AkAtQ_reTVhFNSESQaawRkZgZS6tFaYczKiTJuSUqEuyVVKG0pBSJAjUi1Dg9viLWLT-aH7wWL5Pl0VVRq6r3oIsWjzW2GfQtxiSsW8b_aZC32xDIfvx5gz6ZpctPU24c2pjsnHU7WevZSL1-f5bLooPed8KC3qFlWNtQHBvUBjrbFYf-ZFG6UVWJAejWSKaa8aFFrWyBGN8k3NhUc-JvfHvrsYvveYBrcJ-9jnkQ60MVxzSnmm6JHyMaQUsXW7mK-Jvw6oO8hyWZY7yHInWTlyd4x0iPiPa265lJb_AfPNZPU</recordid><startdate>201606</startdate><enddate>201606</enddate><creator>Zbede, Yaman B.</creator><creator>Gadoue, Shady M.</creator><creator>Atkinson, David J.</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>8FD</scope><scope>L7M</scope></search><sort><creationdate>201606</creationdate><title>Model Predictive MRAS Estimator for Sensorless Induction Motor Drives</title><author>Zbede, Yaman B. ; Gadoue, Shady M. ; Atkinson, David J.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c333t-9e7fe6aea8143c4e89989eab155d6761915ce852627c6de475ae3ee86cda34ce3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Adaptation models</topic><topic>Cost function</topic><topic>induction motor drive</topic><topic>Inverters</topic><topic>Mathematical model</topic><topic>Model reference adaptive control</topic><topic>Motors</topic><topic>Performance evaluation</topic><topic>position estimation</topic><topic>Predictive control</topic><topic>Rotors</topic><topic>speed estimation</topic><topic>Stators</topic><topic>vector control</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zbede, Yaman B.</creatorcontrib><creatorcontrib>Gadoue, Shady M.</creatorcontrib><creatorcontrib>Atkinson, David J.</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998–Present</collection><collection>IEEE Xplore</collection><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>IEEE transactions on industrial electronics (1982)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zbede, Yaman B.</au><au>Gadoue, Shady M.</au><au>Atkinson, David J.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Model Predictive MRAS Estimator for Sensorless Induction Motor Drives</atitle><jtitle>IEEE transactions on industrial electronics (1982)</jtitle><stitle>TIE</stitle><date>2016-06</date><risdate>2016</risdate><volume>63</volume><issue>6</issue><spage>3511</spage><epage>3521</epage><pages>3511-3521</pages><issn>0278-0046</issn><eissn>1557-9948</eissn><coden>ITIED6</coden><abstract>This paper presents a novel predictive model reference adaptive system (MRAS) speed estimator for sensorless induction motor (IM) drives applications. The proposed estimator is based on the finite control set-model predictive control (FCS-MPC) principle. The rotor position is calculated using a search-based optimization algorithm which ensures a minimum speed tuning error signal at each sampling period. This eliminates the need for a proportional-integral (PI) controller which is conventionally employed in the adaption mechanism of MRAS estimators. Extensive experimental tests have been carried out to evaluate the performance of the proposed estimator using a 2.2-kW IM with a field-oriented control (FOC) scheme employed as the motor control strategy. Experimental results show improved performance of the MRAS scheme in both open- and closed-loop sensorless modes of operation at low speeds and with different loading conditions including regeneration. The proposed scheme also improves the system robustness against motor parameter variations and increases the maximum bandwidth of the speed loop controller.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TIE.2016.2521721</doi><tpages>11</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Adaptation models Cost function induction motor drive Inverters Mathematical model Model reference adaptive control Motors Performance evaluation position estimation Predictive control Rotors speed estimation Stators vector control |
title | Model Predictive MRAS Estimator for Sensorless Induction Motor Drives |
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