Implementation of Artificial Neural Network-Based Tracking Controller for High-Performance Stepper Motor Drives
Two distinct multilayer perception neural networks (NNs) are implemented via laboratory experiment to simultaneously identify and adaptively control the trajectory tracking of a hybrid step motor assumed to operate in a high-performance drives environment. That is, a neural network identifier (NNI)...
Saved in:
Published in | IEEE transactions on industrial electronics (1982) Vol. 54; no. 1; pp. 218 - 227 |
---|---|
Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
New York
IEEE
01.02.2007
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subjects | |
Online Access | Get full text |
Cover
Loading…
Abstract | Two distinct multilayer perception neural networks (NNs) are implemented via laboratory experiment to simultaneously identify and adaptively control the trajectory tracking of a hybrid step motor assumed to operate in a high-performance drives environment. That is, a neural network identifier (NNI) which captures the nonlinear dynamics of the stepper motor drive system (SMDS) over any arbitrary time interval in its range of operation, and a neural network controller (NNC) to provide the necessary control actions as to achieve trajectory tracking of the rotor speed. The exact form of the control law is unknown, and must be estimated by the NNC. Consequently, the NNC is constructed as a nonlinear unknown function depending on the current state of the drive system supplies by the NNI and the reference trajectory we wish the outputs to follow. The two NNs are online trained using dynamic back-propagation algorithm. The composite structure is used as a speed controller for the SMDS. Performance of the composite controller is evaluated through a laboratory experiment. Experimental results show the effectiveness of this approach, and demonstrate the usefulness of the proposed controller in high-performance drives |
---|---|
AbstractList | Two distinct multilayer perception neural networks (NNs) are implemented via laboratory experiment to simultaneously identify and adaptively control the trajectory tracking of a hybrid step motor assumed to operate in a high-performance drives environment. That is, a neural network identifier (NNI) which captures the nonlinear dynamics of the stepper motor drive system (SMDS) over any arbitrary time interval in its range of operation, and a neural network controller (NNC) to provide the necessary control actions as to achieve trajectory tracking of the rotor speed. The exact form of the control law is unknown, and must be estimated by the NNC. Consequently, the NNC is constructed as a nonlinear unknown function depending on the current state of the drive system supplies by the NNI and the reference trajectory we wish the outputs to follow. The two NNs are online trained using dynamic back-propagation algorithm. The composite structure is used as a speed controller for the SMDS. Performance of the composite controller is evaluated through a laboratory experiment. Experimental results show the effectiveness of this approach, and demonstrate the usefulness of the proposed controller in high-performance drives [...] the NNC is constructed as a nonlinear unknown function depending on the current state of the drive system supplies by the NNI and the reference trajectory we wish the outputs to follow. Two distinct multilayer perception neural networks (NNs) are implemented via laboratory experiment to simultaneously identify and adaptively control the trajectory tracking of a hybrid step motor assumed to operate in a high- performance drives [abstract truncated by publisher]. |
Author | Garuba, M. Castro-Sitiriche, M.J. Burge, L. Rubaai, A. |
Author_xml | – sequence: 1 givenname: A. surname: Rubaai fullname: Rubaai, A. organization: Electr. & Comput. Eng. Dept., Howard Univ., Washington, DC – sequence: 2 givenname: M.J. surname: Castro-Sitiriche fullname: Castro-Sitiriche, M.J. organization: Electr. & Comput. Eng. Dept., Howard Univ., Washington, DC – sequence: 3 givenname: M. surname: Garuba fullname: Garuba, M. – sequence: 4 givenname: L. surname: Burge fullname: Burge, L. |
BookMark | eNp9kb1vFDEQxa0oSLkc1BRpVikCzV78tV67DEcgJ4UPiaO2vN7ZxMmuvbF9IP57fByioEgzM9L85klv3ik69sEDQq8JXhGC1eV2c72iGIuVlLKVzRFakKZpa6W4PEYLTFtZY8zFCTpN6QFjwhvSLFDYTPMIE_hssgu-CkN1FbMbnHVmrD7DLv5p-WeIj_U7k6CvttHYR-fvqnXwOYZxhFgNIVY37u6-_gqxzJPxFqpvGea5LD-FXNbvo_sB6SV6MZgxwau_fYm-f7jerm_q2y8fN-ur29oyyXOpPTei71QLTDBO-65tOEg6WDMYMIr0tmu46buhOG4pM9QS2VlLRNdJagxbojcH3TmGpx2krCeXLIyj8RB2SSvMBFVCyUJePEsyzhtGqCrg22dBIlpSvowZL-j5f-hD2EVfDGspOJZC8r3e5QGyMaQUYdBzdJOJvzTBeh-pLpHqfaT6EGm5ODtcOAD4Rxc9LpRivwH2Ap_g |
CODEN | ITIED6 |
CitedBy_id | crossref_primary_10_1016_j_enconman_2010_09_021 crossref_primary_10_1080_15325008_2012_658600 crossref_primary_10_1109_TIE_2014_2356439 crossref_primary_10_1007_s11460_012_0211_1 crossref_primary_10_1109_TIE_2008_2003319 crossref_primary_10_1007_s12555_021_0371_y crossref_primary_10_1109_TPEL_2010_2046648 crossref_primary_10_1109_TIE_2011_2114314 crossref_primary_10_1109_TIE_2008_2008791 crossref_primary_10_1016_j_jestch_2020_09_008 crossref_primary_10_1016_j_jfranklin_2021_03_006 crossref_primary_10_3390_en15031222 crossref_primary_10_1109_CJECE_2018_2849357 crossref_primary_10_3390_en13184939 crossref_primary_10_1109_TPEL_2018_2878928 crossref_primary_10_1109_TII_2012_2221722 crossref_primary_10_1049_iet_rpg_2019_0601 crossref_primary_10_1109_TPEL_2010_2102367 crossref_primary_10_1109_TIE_2009_2037650 crossref_primary_10_1109_TIE_2007_905929 crossref_primary_10_1109_TIE_2018_2793214 crossref_primary_10_1007_s10015_015_0252_7 crossref_primary_10_1016_j_compeleceng_2019_106535 crossref_primary_10_1016_j_epsr_2014_10_004 crossref_primary_10_1109_TIE_2008_918392 crossref_primary_10_20965_jaciii_2009_p0025 crossref_primary_10_1016_j_epsr_2016_05_007 |
Cites_doi | 10.1109/21.278990 10.1109/CDC.1990.203409 10.1109/TIE.2004.824878 10.1109/28.913715 10.1109/41.847902 10.1109/72.80202 10.1109/IECON.2002.1185303 10.1109/28.993166 10.1109/IJCNN.1990.137819 10.1109/IECON.2001.976453 10.1109/9.76368 10.1109/60.507646 10.1109/87.221347 10.1109/72.822511 10.1109/3477.826961 10.1109/28.845075 10.1109/CDC.2000.912117 10.1109/2943.384663 10.1109/41.915421 10.1109/TSMCC.2002.1009125 10.1109/FUZZ.2001.1007270 10.1109/70.68082 10.1109/7.766933 10.1109/ISIE.2002.1026083 |
ContentType | Journal Article |
Copyright | Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2007 |
Copyright_xml | – notice: Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2007 |
DBID | 97E RIA RIE AAYXX CITATION 7SP 8FD L7M F28 FR3 |
DOI | 10.1109/TIE.2006.888785 |
DatabaseName | IEEE All-Society Periodicals Package (ASPP) 2005-present IEEE All-Society Periodicals Package (ASPP) Online IEL CrossRef Electronics & Communications Abstracts Technology Research Database Advanced Technologies Database with Aerospace ANTE: Abstracts in New Technology & Engineering Engineering Research Database |
DatabaseTitle | CrossRef Technology Research Database Advanced Technologies Database with Aerospace Electronics & Communications Abstracts Engineering Research Database ANTE: Abstracts in New Technology & Engineering |
DatabaseTitleList | Technology Research Database Engineering Research Database Engineering Research Database Engineering Research Database |
Database_xml | – sequence: 1 dbid: RIE name: IEEE url: https://proxy.k.utb.cz/login?url=https://ieeexplore.ieee.org/ sourceTypes: Publisher |
DeliveryMethod | fulltext_linktorsrc |
Discipline | Engineering |
EISSN | 1557-9948 |
EndPage | 227 |
ExternalDocumentID | 2333681751 10_1109_TIE_2006_888785 4084699 |
Genre | orig-research |
GroupedDBID | -~X .DC 0R~ 29I 4.4 5GY 5VS 6IK 97E 9M8 AAJGR AASAJ ABQJQ ABVLG ACGFO ACGFS ACIWK ACKIV ACNCT AENEX AETIX AI. AIBXA AKJIK ALLEH ALMA_UNASSIGNED_HOLDINGS ASUFR ATWAV BEFXN BFFAM BGNUA BKEBE BPEOZ CS3 DU5 EBS EJD HZ~ H~9 IBMZZ ICLAB IFIPE IFJZH IPLJI JAVBF LAI M43 MS~ O9- OCL P2P RIA RIE RIG RNS TAE TN5 TWZ VH1 VJK XFK AAYXX CITATION 7SP 8FD L7M F28 FR3 |
ID | FETCH-LOGICAL-c384t-c3d4a6db97e36342db754e82fcafaea91dcb54adbf006723a2c18bcc16bb82aa3 |
IEDL.DBID | RIE |
ISSN | 0278-0046 |
IngestDate | Fri Aug 16 08:45:40 EDT 2024 Fri Aug 16 10:26:08 EDT 2024 Fri Aug 16 09:45:36 EDT 2024 Thu Oct 10 18:15:30 EDT 2024 Fri Aug 23 01:04:22 EDT 2024 Wed Jun 26 19:26:42 EDT 2024 |
IsPeerReviewed | true |
IsScholarly | true |
Issue | 1 |
Language | English |
LinkModel | DirectLink |
MergedId | FETCHMERGED-LOGICAL-c384t-c3d4a6db97e36342db754e82fcafaea91dcb54adbf006723a2c18bcc16bb82aa3 |
Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 ObjectType-Article-2 ObjectType-Feature-1 |
PQID | 864086849 |
PQPubID | 23500 |
PageCount | 10 |
ParticipantIDs | proquest_miscellaneous_34453129 ieee_primary_4084699 proquest_miscellaneous_1671278034 proquest_journals_864086849 proquest_miscellaneous_903629698 crossref_primary_10_1109_TIE_2006_888785 |
PublicationCentury | 2000 |
PublicationDate | 2007-02-01 |
PublicationDateYYYYMMDD | 2007-02-01 |
PublicationDate_xml | – month: 02 year: 2007 text: 2007-02-01 day: 01 |
PublicationDecade | 2000 |
PublicationPlace | New York |
PublicationPlace_xml | – name: New York |
PublicationTitle | IEEE transactions on industrial electronics (1982) |
PublicationTitleAbbrev | TIE |
PublicationYear | 2007 |
Publisher | IEEE The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher_xml | – name: IEEE – name: The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
References | ref13 ref12 laid (ref18) 2001; 1 ref15 ref14 ref30 ref11 ref10 (ref28) 2002 ref2 ref1 ref17 ref16 ref19 (ref27) 2004 ref24 (ref29) 2000 ref23 ref25 ref20 ref22 ref21 betin (ref7) 1999; 8 ref8 ref9 ref4 ref3 ref6 ref5 (ref26) 1998 |
References_xml | – ident: ref13 doi: 10.1109/21.278990 – ident: ref6 doi: 10.1109/CDC.1990.203409 – ident: ref17 doi: 10.1109/TIE.2004.824878 – ident: ref9 doi: 10.1109/28.913715 – ident: ref11 doi: 10.1109/41.847902 – ident: ref12 doi: 10.1109/72.80202 – ident: ref23 doi: 10.1109/IECON.2002.1185303 – ident: ref10 doi: 10.1109/28.993166 – ident: ref30 doi: 10.1109/IJCNN.1990.137819 – ident: ref24 doi: 10.1109/IECON.2001.976453 – ident: ref4 doi: 10.1109/9.76368 – year: 2000 ident: ref29 publication-title: HMPCI-DAS6402_16 Technical Manual Data – ident: ref8 doi: 10.1109/60.507646 – ident: ref5 doi: 10.1109/87.221347 – volume: 1 start-page: 1504 year: 2001 ident: ref18 article-title: vector control of hybrid stepping motor position servo system using neural network control publication-title: Proc IEEE IECON 01 Conf contributor: fullname: laid – ident: ref16 doi: 10.1109/72.822511 – ident: ref15 doi: 10.1109/3477.826961 – volume: 8 start-page: 33 year: 1999 ident: ref7 article-title: closed loop control of stepping motor drive: comparison between pid control, self-tuning regulation and fuzzy logic control publication-title: Eur Power Electron J contributor: fullname: betin – year: 2002 ident: ref28 publication-title: HMPCI-CTR05 Technical Manual Data – year: 2004 ident: ref27 publication-title: E3-69-2500CPR Technical Manual Data – year: 1998 ident: ref26 publication-title: JT91338Rev1 Technical Data Manual – ident: ref25 doi: 10.1109/28.845075 – ident: ref19 doi: 10.1109/CDC.2000.912117 – ident: ref2 doi: 10.1109/2943.384663 – ident: ref14 doi: 10.1109/41.915421 – ident: ref20 doi: 10.1109/TSMCC.2002.1009125 – ident: ref21 doi: 10.1109/FUZZ.2001.1007270 – ident: ref1 doi: 10.1109/70.68082 – ident: ref3 doi: 10.1109/7.766933 – ident: ref22 doi: 10.1109/ISIE.2002.1026083 |
SSID | ssj0014515 |
Score | 2.096935 |
Snippet | Two distinct multilayer perception neural networks (NNs) are implemented via laboratory experiment to simultaneously identify and adaptively control the... [...] the NNC is constructed as a nonlinear unknown function depending on the current state of the drive system supplies by the NNI and the reference... |
SourceID | proquest crossref ieee |
SourceType | Aggregation Database Publisher |
StartPage | 218 |
SubjectTerms | Artificial neural network (NN) Artificial neural networks Control systems dynamic back-propagation (DBP) Dynamical systems Heuristic algorithms model reference adaptive control Motor drives Motors Multi-layer neural network Neural networks Nonlinear control systems Nonlinear dynamical systems Nonlinear dynamics Rotors stepper motor Steppers Studies Tracking Trajectories Trajectory |
Title | Implementation of Artificial Neural Network-Based Tracking Controller for High-Performance Stepper Motor Drives |
URI | https://ieeexplore.ieee.org/document/4084699 https://www.proquest.com/docview/864086849 https://search.proquest.com/docview/1671278034 https://search.proquest.com/docview/34453129 https://search.proquest.com/docview/903629698 |
Volume | 54 |
hasFullText | 1 |
inHoldings | 1 |
isFullTextHit | |
isPrint | |
link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV1LT9wwEB4BJ3roi1bd0ocrceDQLLHjOPaxUBBU2ooDSNwiPyaXtgladi_8esZ2dosoSL0kkWYUWR7bM-OZ-QZgT1qFQlksutKGgvS1K5zzvBA1ooldKisXa4dnP9XppfxxVV9twNd1LQwipuQznMbPFMsPg1_Gq7IDWZK2NGYTNnUpcq3WOmIg69ytQETEWHL6RhgfXpqDi7PjHHUgb6-JTZPvaaDUUuWfczgpl5MXMFsNK-eU_JouF27qbx8gNv7vuF_C89HKZN_ysngFG9i_hmf3sAd3YEi4wH_G0qOeDV1iz4ASLGJ2pFdKEi8OSdcFRnrNx5t1dpTz23_jnJHNy2KuSHH-twKBxdSxayLOBvLo2fd5hLZ9A5cnxxdHp8XYfaHwlZYLegYSZHCmwUpVUgTX1BK16LztLFrDg3e1tMF1KZxbWeG5dt5z5ZwW1lZvYasfenwHTLuOaxvIOQsobcMd2XmdRl9qr7HuygnsryTSXmeQjTY5J6VpSXixVaZqs_AmsBPnd802Tu0EdlcSbMdNeNNqRVSlJVG_rKm0e2JIxPY4LG9arhpOK6as5AQ-P8FTSUkHlaC_sCc4TDQDjDL6_eOj24XtfCUcs2A-wNZivsSPZMss3Ke0iO8AI6L1Bw |
link.rule.ids | 315,786,790,802,27955,27956,55107 |
linkProvider | IEEE |
linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV1Lb9QwEB6VcoAeWqAglhZqJA4cyDZOHMc-ltJqC92Kw1bqLfJjcikk1Xb30l_P2M4uFVCJSxJpRpHlsT0znplvAD4II7GQBrM2Nz4jfW0zax3PigpRhy6VpQ21w9MLObkUX6-qqw34tK6FQcSYfIbj8Blj-b53y3BVdihy0pZaP4LHpOfzOlVrrWMGokr9CoqAGUtu3wDkw3N9ODs7SXEH8vfq0Db5ng6KTVX-OomjejndgelqYCmr5Hq8XNixu_sDs_F_R_4Mtgc7kx2lhfEcNrB7AVv30Ad3oY_IwD-H4qOO9W1kT5ASLKB2xFdME88-k7bzjDSbC3fr7DhluP_AOSOrl4Vskez77xoEFpLHbog47cmnZ1_mAdz2JVyensyOJ9nQfyFzpRILenoSpbe6xlKWovC2rgSqonWmNWg0985WwnjbxoBuaQrHlXWOS2tVYUz5Cja7vsPXwJRtuTKe3DOPwtTckqXXKnS5cgqrNh_Bx5VEmpsEs9FE9yTXDQkvNMuUTRLeCHbD_K7Zhqkdwd5Kgs2wDW8bJYkqlSDq-zWV9k8IipgO--Vtw2XNacXkpRjBwQM8pRB0VBX0F_YAhw6GgJZavfn36A7gyWQ2PW_Ozy6-7cHTdEEccmL2YXMxX-JbsmwW9l1c0L8AKYz4Ww |
openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Implementation+of+Artificial+Neural+Network-Based+Tracking+Controller+for+High-Performance+Stepper+Motor+Drives&rft.jtitle=IEEE+transactions+on+industrial+electronics+%281982%29&rft.au=Rubaai%2C+A&rft.au=Castro-Sitiriche%2C+MJ&rft.au=Garuba%2C+M&rft.au=Burge%2C+L&rft.date=2007-02-01&rft.issn=0278-0046&rft.volume=54&rft.issue=1&rft_id=info:doi/10.1109%2FTIE.2006.888785&rft.externalDBID=NO_FULL_TEXT |
thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0278-0046&client=summon |
thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0278-0046&client=summon |
thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0278-0046&client=summon |