{"id":"https://openalex.org/W7092660147","doi":"https://doi.org/10.1109/access.2025.3623889","title":"A Novel Semi-Supervisory Neural Network Approach for Fault Estimation in Steer-By-Wire Electric Motors","display_name":"A Novel Semi-Supervisory Neural Network Approach for Fault Estimation in Steer-By-Wire Electric Motors","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W7092660147","doi":"https://doi.org/10.1109/access.2025.3623889"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3623889","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3623889","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2025.3623889","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Daeyi Jung","orcid":"https://orcid.org/0000-0002-2043-7045"},"institutions":[{"id":"https://openalex.org/I120158604","display_name":"Kunsan National University","ror":"https://ror.org/02yj55q56","country_code":"KR","type":"education","lineage":["https://openalex.org/I120158604"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Daeyi Jung","raw_affiliation_strings":["Kunsan National University, Gunsan-si, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-2043-7045","affiliations":[{"raw_affiliation_string":"Kunsan National University, Gunsan-si, South Korea","institution_ids":["https://openalex.org/I120158604"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I120158604"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":3.079,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.9355756,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"13","issue":null,"first_page":"184850","last_page":"184864"},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T10978","display_name":"Prenatal Screening and Diagnostics","score":0.0723000019788742,"subfield":{"id":"https://openalex.org/subfields/2735","display_name":"Pediatrics, Perinatology and Child Health"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10978","display_name":"Prenatal Screening and Diagnostics","score":0.0723000019788742,"subfield":{"id":"https://openalex.org/subfields/2735","display_name":"Pediatrics, Perinatology and Child Health"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11732","display_name":"Assisted Reproductive Technology and Twin Pregnancy","score":0.04390000179409981,"subfield":{"id":"https://openalex.org/subfields/2735","display_name":"Pediatrics, Perinatology and Child Health"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T12552","display_name":"Fetal and Pediatric Neurological Disorders","score":0.01860000006854534,"subfield":{"id":"https://openalex.org/subfields/2735","display_name":"Pediatrics, Perinatology and Child Health"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7211999893188477},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5705999732017517},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.5303000211715698},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.5285999774932861},{"id":"https://openalex.org/keywords/observer","display_name":"Observer (physics)","score":0.460099995136261},{"id":"https://openalex.org/keywords/fault-tolerance","display_name":"Fault tolerance","score":0.4075999855995178},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.36340001225471497},{"id":"https://openalex.org/keywords/induction-motor","display_name":"Induction motor","score":0.3605000078678131}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7328000068664551},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7211999893188477},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5705999732017517},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.5303000211715698},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.5285999774932861},{"id":"https://openalex.org/C2780704645","wikidata":"https://www.wikidata.org/wiki/Q9251458","display_name":"Observer (physics)","level":2,"score":0.460099995136261},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.41260001063346863},{"id":"https://openalex.org/C63540848","wikidata":"https://www.wikidata.org/wiki/Q3140932","display_name":"Fault tolerance","level":2,"score":0.4075999855995178},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.36340001225471497},{"id":"https://openalex.org/C80962145","wikidata":"https://www.wikidata.org/wiki/Q207450","display_name":"Induction motor","level":3,"score":0.3605000078678131},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.3287000060081482},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.32820001244544983},{"id":"https://openalex.org/C52970973","wikidata":"https://www.wikidata.org/wiki/Q2497134","display_name":"Adaptive system","level":2,"score":0.3273000121116638},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.31130000948905945},{"id":"https://openalex.org/C152745839","wikidata":"https://www.wikidata.org/wiki/Q5438153","display_name":"Fault detection and isolation","level":3,"score":0.30660000443458557},{"id":"https://openalex.org/C183356978","wikidata":"https://www.wikidata.org/wiki/Q1779213","display_name":"Tracking error","level":3,"score":0.2964000105857849},{"id":"https://openalex.org/C176871988","wikidata":"https://www.wikidata.org/wiki/Q72313","display_name":"Electric motor","level":2,"score":0.28349998593330383},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.26739999651908875},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.2671000063419342},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.26420000195503235},{"id":"https://openalex.org/C2776365744","wikidata":"https://www.wikidata.org/wiki/Q5438149","display_name":"Fault Simulator","level":5,"score":0.25110000371932983}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2025.3623889","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3623889","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:ba25e2c9d04a4d5f85b8c7c6f1f0c591","is_oa":true,"landing_page_url":"https://doaj.org/article/ba25e2c9d04a4d5f85b8c7c6f1f0c591","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 13, Pp 184850-184864 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3623889","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3623889","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"This":[0,123,185],"paper":[1],"presents":[2],"a":[3,17,29,87,101,120,143,225,288,303],"novel":[4],"fault":[5,47,91,202,253],"estimation":[6,39,66,81,183,209,245,293],"strategy":[7],"for":[8,308],"electric":[9],"motors":[10],"in":[11,54,152,200,205,280],"Steer-By-Wire":[12],"(SBW)":[13],"systems,":[14],"based":[15],"on":[16,224],"Semi-Supervisory":[18],"Artificial":[19],"Neural":[20],"Network":[21],"(SSANN)":[22],"observer.":[23],"Our":[24],"previous":[25],"work":[26],"[22]":[27],"explored":[28],"purely":[30,266],"supervisory":[31,172,267],"ANN-based":[32],"approach":[33,51],"(SANN),":[34],"which":[35,137,259],"demonstrated":[36],"significantly":[37,236],"improved":[38],"performance":[40,82],"over":[41],"traditional":[42],"model-based":[43],"methods":[44],"under":[45],"various":[46],"scenarios.":[48],"However,":[49],"this":[50],"showed":[52],"limitations":[53],"accurately":[55],"tracking":[56],"high-frequency":[57],"faults":[58],"and":[59,83,95,114,135,207,222,283,294,305],"adapting":[60,196],"to":[61,78,149,190,197,263,287],"unexpected":[62],"perturbations":[63],"throughout":[64],"the":[65,72,106,111,160,170,181,188,201,238,275],"process.":[67],"To":[68],"address":[69],"these":[70],"challenges,":[71],"proposed":[73,161,212],"SSANN":[74,99,162,235,250,276],"architecture":[75],"is":[76,108,125,270,278],"introduced":[77],"further":[79],"enhance":[80],"ensure":[84],"robustness":[85],"across":[86],"broader":[88],"range":[89,290],"of":[90,132,291],"scenarios,":[92],"including":[93],"chirp-like":[94],"step-like":[96],"signals.":[97],"The":[98,211],"employs":[100],"hybrid":[102],"adaptive":[103,164],"structure,":[104],"where":[105],"network":[107],"initialized":[109],"with":[110,228,255,297],"pre-trained":[112],"weights":[113,134],"biases":[115],"from":[116,169],"SANN,":[117],"serving":[118],"as":[119],"stable":[121],"baseline.":[122],"baseline":[124,171,192],"then":[126],"complemented":[127],"by":[128,247],"an":[129],"additional":[130],"set":[131],"online-adjustable":[133],"biases,":[136],"are":[138,167],"updated":[139],"during":[140],"operation":[141],"using":[142,265],"newly":[144],"designed":[145],"loss":[146],"function":[147],"tailored":[148],"motor":[150],"dynamics":[151],"SBW":[153],"systems.":[154],"Unlike":[155],"conventional":[156],"semi-supervisory":[157],"ANN":[158],"approaches,":[159],"introduces":[163],"parameters":[165],"that":[166,175,234,274],"decoupled":[168],"model,":[173],"ensuring":[174],"online":[176],"learning":[177],"does":[178],"not":[179],"destabilize":[180],"core":[182],"framework.":[184],"design":[186],"enables":[187],"observer":[189],"maintain":[191],"stability":[193],"while":[194],"effectively":[195],"unanticipated":[198],"changes":[199],"signal,":[203],"resulting":[204],"robust":[206],"accurate":[208],"performance.":[210],"method":[213],"has":[214],"been":[215],"rigorously":[216],"validated":[217],"through":[218],"Hardware-in-the-Loop":[219],"Simulation":[220],"(HILS)":[221],"testing":[223],"compact":[226],"simulator":[227],"human":[229],"participants.":[230],"Experimental":[231],"results":[232],"confirm":[233],"outperforms":[237],"original":[239],"SANN":[240],"approach,":[241],"reducing":[242],"final":[243],"cumulative":[244],"error":[246],"25\u201341%.":[248],"Furthermore,":[249],"successfully":[251],"captures":[252],"signals":[254],"higher":[256],"frequency":[257],"components,":[258],"were":[260],"previously":[261],"difficult":[262],"estimate":[264],"methods.":[268],"It":[269],"also":[271],"worth":[272],"emphasizing":[273],"framework":[277],"general":[279],"its":[281],"formulation":[282],"can":[284],"be":[285],"applied":[286],"wide":[289],"nonlinear":[292],"control":[295],"problems":[296],"minimal":[298],"structural":[299],"modifications,":[300],"making":[301],"it":[302],"versatile":[304],"practical":[306],"solution":[307],"real-world":[309],"applications.":[310]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-21T00:00:00"}
