{"id":"https://openalex.org/W4294691787","doi":"https://doi.org/10.23919/acc53348.2022.9867798","title":"Learning-based Adaptive-Scenario-Tree Model Predictive Control with Probabilistic Safety Guarantees Using Bayesian Neural Networks","display_name":"Learning-based Adaptive-Scenario-Tree Model Predictive Control with Probabilistic Safety Guarantees Using Bayesian Neural Networks","publication_year":2022,"publication_date":"2022-06-08","ids":{"openalex":"https://openalex.org/W4294691787","doi":"https://doi.org/10.23919/acc53348.2022.9867798"},"language":"en","primary_location":{"id":"doi:10.23919/acc53348.2022.9867798","is_oa":false,"landing_page_url":"https://doi.org/10.23919/acc53348.2022.9867798","pdf_url":null,"source":{"id":"https://openalex.org/S4363607732","display_name":"2022 American Control Conference (ACC)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 American Control Conference (ACC)","raw_type":"proceedings-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/I165733156","display_name":"University of Georgia","ror":"https://ror.org/00te3t702","country_code":"US","type":"education","lineage":["https://openalex.org/I165733156"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yajie Bao","raw_affiliation_strings":["University of Georgia,School of Electrical and Computer Engineering,Athens,GA,USA,30602"],"affiliations":[{"raw_affiliation_string":"University of Georgia,School of Electrical and Computer Engineering,Athens,GA,USA,30602","institution_ids":["https://openalex.org/I165733156"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076120419","display_name":"Kimberly J. Chan","orcid":"https://orcid.org/0000-0002-9460-1653"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kimberly J. Chan","raw_affiliation_strings":["University of California,Department of Chemical and Biomolecular Engineering,Berkeley,CA,USA,94720"],"affiliations":[{"raw_affiliation_string":"University of California,Department of Chemical and Biomolecular Engineering,Berkeley,CA,USA,94720","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101555401","display_name":"Ali Mesbah","orcid":"https://orcid.org/0000-0002-1700-0600"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ali Mesbah","raw_affiliation_strings":["University of California,Department of Chemical and Biomolecular Engineering,Berkeley,CA,USA,94720"],"affiliations":[{"raw_affiliation_string":"University of California,Department of Chemical and Biomolecular Engineering,Berkeley,CA,USA,94720","institution_ids":["https://openalex.org/I95457486"]}]},{"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/I165733156","display_name":"University of Georgia","ror":"https://ror.org/00te3t702","country_code":"US","type":"education","lineage":["https://openalex.org/I165733156"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Javad Mohammadpour Velni","raw_affiliation_strings":["University of Georgia,School of Electrical and Computer Engineering,Athens,GA,USA,30602"],"affiliations":[{"raw_affiliation_string":"University of Georgia,School of Electrical and Computer Engineering,Athens,GA,USA,30602","institution_ids":["https://openalex.org/I165733156"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5058947568"],"corresponding_institution_ids":["https://openalex.org/I165733156"],"apc_list":null,"apc_paid":null,"fwci":3.1852,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.94246714,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"3260","last_page":"3265"},"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":0.9954000115394592,"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/T11236","display_name":"Control Systems and Identification","score":0.9699000120162964,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.7362513542175293},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.735323429107666},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.6320772171020508},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.6023951172828674},{"id":"https://openalex.org/keywords/model-predictive-control","display_name":"Model predictive control","score":0.5698026418685913},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4909398853778839},{"id":"https://openalex.org/keywords/bayesian-network","display_name":"Bayesian network","score":0.48721808195114136},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4843946099281311},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4503617584705353},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4126337170600891},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.2751944065093994},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10290282964706421}],"concepts":[{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.7362513542175293},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.735323429107666},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.6320772171020508},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.6023951172828674},{"id":"https://openalex.org/C172205157","wikidata":"https://www.wikidata.org/wiki/Q1782962","display_name":"Model predictive control","level":3,"score":0.5698026418685913},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4909398853778839},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.48721808195114136},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4843946099281311},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4503617584705353},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4126337170600891},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.2751944065093994},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10290282964706421},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/acc53348.2022.9867798","is_oa":false,"landing_page_url":"https://doi.org/10.23919/acc53348.2022.9867798","pdf_url":null,"source":{"id":"https://openalex.org/S4363607732","display_name":"2022 American Control Conference (ACC)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 American Control Conference (ACC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"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/W1534712813","https://openalex.org/W1591375184","https://openalex.org/W2006859604","https://openalex.org/W2063348960","https://openalex.org/W2067716288","https://openalex.org/W2072991174","https://openalex.org/W2153885307","https://openalex.org/W2619551236","https://openalex.org/W2724171116","https://openalex.org/W2734934093","https://openalex.org/W2769617651","https://openalex.org/W2892521964","https://openalex.org/W2900806034","https://openalex.org/W2992833799","https://openalex.org/W3000508506","https://openalex.org/W3045882693","https://openalex.org/W3046184354","https://openalex.org/W3102735978","https://openalex.org/W3105252106","https://openalex.org/W3120393608","https://openalex.org/W3125192641","https://openalex.org/W4206551089"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4290792893","https://openalex.org/W4306674287","https://openalex.org/W4224009465","https://openalex.org/W4286629047","https://openalex.org/W4306321456","https://openalex.org/W4385957992","https://openalex.org/W2884405396","https://openalex.org/W4319778830","https://openalex.org/W2069572447"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3,24,37,63,105,110,131,138,164],"learning-based":[4],"adaptive-scenario-tree":[5],"model":[6,29,116],"predictive":[7],"control":[8,124,158],"(MPC)":[9],"approach":[10,120,153],"with":[11,104,126,130,143,163],"probabilistic":[12,76],"safety":[13,77],"guarantees":[14,78],"using":[15,36],"Bayesian":[16],"neural":[17],"networks":[18],"(BNNs)":[19],"for":[20,50],"nonlinear":[21],"systems.":[22],"First,":[23],"data-driven":[25],"description":[26,42],"of":[27,59,70,86,93,114],"the":[28,40,57,68,71,84,87,90,94,98,102,115,118,151],"uncertainty":[30],"(i.e.,":[31],"plant-model":[32],"mismatch)":[33],"is":[34,43],"learned":[35,41],"BNN.":[38],"Then,":[39],"employed":[44],"to":[45,66,128,161],"generate":[46],"adaptive":[47],"scenarios":[48,88,100],"online":[49],"scenario-based":[51],"MPC":[52],"(sMPC).":[53],"To":[54],"accurately":[55],"represent":[56],"evolution":[58],"uncertainties,":[60],"we":[61],"use":[62],"moment-matching":[64],"method":[65],"compute":[67],"probabilities":[69],"generated":[72,99],"time-varying":[73],"scenarios.":[74],"Moreover,":[75],"are":[79],"provided":[80],"by":[81],"ensuring":[82],"that":[83,150],"trajectories":[85],"contain":[89],"real":[91],"trajectory":[92],"system":[95,142],"and":[96],"all":[97],"satisfy":[101],"constraints":[103],"high":[106],"probability.":[107],"By":[108],"realizing":[109],"less":[111],"conservative":[112],"estimation":[113],"uncertainty,":[117],"proposed":[119,152],"can":[121],"improve":[122],"robust":[123],"performance":[125,159],"respect":[127],"sMPC":[129,162],"fixed":[132,165],"scenario":[133,166],"tree.":[134,167],"Closed-loop":[135],"simulations":[136],"on":[137],"cold":[139],"atmospheric":[140],"plasma":[141],"prototypical":[144],"applications":[145],"in":[146,155],"(bio)materials":[147],"processing":[148],"demonstrate":[149],"results":[154],"an":[156],"improved":[157],"compared":[160]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
