{"id":"https://openalex.org/W4379620515","doi":"https://doi.org/10.1109/lcsys.2023.3283493","title":"A Hybrid Neural Network Approach for Adaptive Scenario-Based Model Predictive Control in the LPV Framework","display_name":"A Hybrid Neural Network Approach for Adaptive Scenario-Based Model Predictive Control in the LPV Framework","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4379620515","doi":"https://doi.org/10.1109/lcsys.2023.3283493"},"language":"en","primary_location":{"id":"doi:10.1109/lcsys.2023.3283493","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lcsys.2023.3283493","pdf_url":null,"source":{"id":"https://openalex.org/S4306422535","display_name":"IEEE Control Systems Letters","issn_l":"2475-1456","issn":["2475-1456"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Control Systems Letters","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5058947568","display_name":"Yajie Bao","orcid":"https://orcid.org/0000-0001-8773-926X"},"institutions":[{"id":"https://openalex.org/I8078737","display_name":"Clemson University","ror":"https://ror.org/037s24f05","country_code":"US","type":"education","lineage":["https://openalex.org/I8078737"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yajie Bao","raw_affiliation_strings":["Department of Mechanical Engineering, Clemson University, Clemson, SC, USA"],"raw_orcid":"https://orcid.org/0000-0001-8773-926X","affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, Clemson University, Clemson, SC, USA","institution_ids":["https://openalex.org/I8078737"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086596463","display_name":"Javad Mohammadpour Velni","orcid":"https://orcid.org/0000-0001-8546-221X"},"institutions":[{"id":"https://openalex.org/I8078737","display_name":"Clemson University","ror":"https://ror.org/037s24f05","country_code":"US","type":"education","lineage":["https://openalex.org/I8078737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Javad Mohammadpour Velni","raw_affiliation_strings":["Department of Mechanical Engineering, Clemson University, Clemson, SC, USA"],"raw_orcid":"https://orcid.org/0000-0001-8546-221X","affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, Clemson University, Clemson, SC, USA","institution_ids":["https://openalex.org/I8078737"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5058947568"],"corresponding_institution_ids":["https://openalex.org/I8078737"],"apc_list":null,"apc_paid":null,"fwci":1.2554,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.79158429,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"7","issue":null,"first_page":"1921","last_page":"1926"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10791","display_name":"Advanced Control Systems Optimization","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10791","display_name":"Advanced Control Systems Optimization","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10820","display_name":"Fuzzy Logic and Control Systems","score":0.9749000072479248,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6698494553565979},{"id":"https://openalex.org/keywords/model-predictive-control","display_name":"Model predictive control","score":0.6268423199653625},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.573517918586731},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.5630417466163635},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.5037028193473816},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5002963542938232},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.4756602644920349},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.41897711157798767},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.343619167804718},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.26060330867767334},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10304364562034607}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6698494553565979},{"id":"https://openalex.org/C172205157","wikidata":"https://www.wikidata.org/wiki/Q1782962","display_name":"Model predictive control","level":3,"score":0.6268423199653625},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.573517918586731},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.5630417466163635},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.5037028193473816},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5002963542938232},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.4756602644920349},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.41897711157798767},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.343619167804718},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.26060330867767334},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10304364562034607},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lcsys.2023.3283493","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lcsys.2023.3283493","pdf_url":null,"source":{"id":"https://openalex.org/S4306422535","display_name":"IEEE Control Systems Letters","issn_l":"2475-1456","issn":["2475-1456"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Control Systems Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8435452092","display_name":null,"funder_award_id":"CMMI-2302219","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W209497275","https://openalex.org/W1490324987","https://openalex.org/W1553000336","https://openalex.org/W2067716288","https://openalex.org/W2072991174","https://openalex.org/W2117781171","https://openalex.org/W2164411961","https://openalex.org/W2170990015","https://openalex.org/W2194401498","https://openalex.org/W2797183175","https://openalex.org/W2892521964","https://openalex.org/W2910717362","https://openalex.org/W3045882693","https://openalex.org/W3102735978","https://openalex.org/W3151678943","https://openalex.org/W4294691787","https://openalex.org/W4312204961","https://openalex.org/W4376644898","https://openalex.org/W6608504065","https://openalex.org/W6684488266","https://openalex.org/W6750580522","https://openalex.org/W6757790240"],"related_works":["https://openalex.org/W1990079087","https://openalex.org/W2060165215","https://openalex.org/W2101188133","https://openalex.org/W3202234113","https://openalex.org/W4248731570","https://openalex.org/W2320869598","https://openalex.org/W4323768008","https://openalex.org/W2381210024","https://openalex.org/W2384015130","https://openalex.org/W2094121346"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,28,45,80,112,132,173],"hybrid":[4,159],"neural":[5,31],"network":[6,32],"(NN)":[7],"approach":[8,139],"for":[9,117],"adaptive":[10],"scenario-based":[11],"model":[12,35,71,142,162],"predictive":[13],"control":[14,166],"(SMPC)":[15],"design":[16],"of":[17,76,95,100,121,131,145],"nonlinear":[18,146],"systems":[19,147],"in":[20],"the":[21,41,53,56,59,69,74,87,93,98,101,106,109,118,122,128,137,143,154,158,165,170],"linear":[22],"parametervarying":[23],"(LPV)":[24],"framework.":[25],"In":[26],"particular,":[27],"deterministic":[29],"artificial":[30],"(ANN)-based":[33],"LPV":[34],"is":[36,49,84],"learned":[37],"from":[38],"data":[39],"as":[40],"nominal":[42],"model.":[43,61],"Then,":[44],"Bayesian":[46],"NN":[47,160],"(BNN)":[48],"used":[50],"to":[51,72,169],"describe":[52],"mismatch":[54],"between":[55],"plant":[57],"and":[58,103,153],"LPV-ANN":[60],"Adaptive":[62],"scenarios":[63,96,107],"are":[64,124],"generated":[65],"online":[66],"based":[67,156],"on":[68,127,157],"BNN":[70],"reduce":[73],"conservativeness":[75],"scenario":[77,88,175],"generation.":[78],"Moreover,":[79],"probabilistic":[81],"safety":[82],"certificate":[83],"incorporated":[85],"into":[86],"generation":[89],"by":[90],"ensuring":[91],"that":[92,104,136],"trajectories":[94],"contain":[97],"trajectory":[99],"system":[102,134],"all":[105],"satisfy":[108],"constraints":[110],"with":[111,172],"high":[113],"probability.":[114],"Furthermore,":[115],"conditions":[116],"recursive":[119],"feasibility":[120],"SMPC":[123,155,171],"given.":[125],"Experiments":[126],"closed-loop":[129],"simulations":[130],"two-tank":[133],"demonstrate":[135],"proposed":[138],"can":[140,163],"better":[141],"behaviors":[144],"than":[148],"sole":[149],"ANN/BNN":[150],"models":[151],"can,":[152],"(HyNN)":[161],"improve":[164],"performance":[167],"compared":[168],"fixed":[174],"tree.":[176]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}