{"id":"https://openalex.org/W7160851414","doi":"https://doi.org/10.48550/arxiv.2605.07801","title":"Sampling-based Model Predictive Control Using Trust Regions","display_name":"Sampling-based Model Predictive Control Using Trust Regions","publication_year":2026,"publication_date":"2026-05-08","ids":{"openalex":"https://openalex.org/W7160851414","doi":"https://doi.org/10.48550/arxiv.2605.07801"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.07801","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.07801","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.07801","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135868183","display_name":"Markus Walker","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Walker, Markus","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135862444","display_name":"Marcel Reith-Braun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Reith-Braun, Marcel","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135831299","display_name":"Daniel Frisch","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Frisch, Daniel","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5055331421","display_name":"Uwe D. Hanebeck","orcid":"https://orcid.org/0000-0001-9870-2331"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hanebeck, Uwe D.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10791","display_name":"Advanced Control Systems Optimization","score":0.9480000138282776,"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":0.9480000138282776,"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":0.016300000250339508,"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/T11206","display_name":"Model Reduction and Neural Networks","score":0.005799999926239252,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/heuristics","display_name":"Heuristics","score":0.6402999758720398},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.6258000135421753},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.5848000049591064},{"id":"https://openalex.org/keywords/model-predictive-control","display_name":"Model predictive control","score":0.5665000081062317},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5304999947547913},{"id":"https://openalex.org/keywords/divergence","display_name":"Divergence (linguistics)","score":0.519599974155426},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.4846999943256378},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.4781999886035919},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.45249998569488525}],"concepts":[{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.6402999758720398},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.6258000135421753},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.607699990272522},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.5848000049591064},{"id":"https://openalex.org/C172205157","wikidata":"https://www.wikidata.org/wiki/Q1782962","display_name":"Model predictive control","level":3,"score":0.5665000081062317},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5304999947547913},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5198000073432922},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.519599974155426},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.4846999943256378},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.4781999886035919},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.45249998569488525},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.43529999256134033},{"id":"https://openalex.org/C171752962","wikidata":"https://www.wikidata.org/wiki/Q255166","display_name":"Kullback\u2013Leibler divergence","level":2,"score":0.4124999940395355},{"id":"https://openalex.org/C91575142","wikidata":"https://www.wikidata.org/wiki/Q1971426","display_name":"Optimal control","level":2,"score":0.38659998774528503},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.34049999713897705},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3287999927997589},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3199000060558319},{"id":"https://openalex.org/C89109886","wikidata":"https://www.wikidata.org/wiki/Q1535924","display_name":"Trust region","level":3,"score":0.3176000118255615},{"id":"https://openalex.org/C83247935","wikidata":"https://www.wikidata.org/wiki/Q7234227","display_name":"Posterior predictive distribution","level":5,"score":0.3046000003814697},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.29919999837875366},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.29899999499320984},{"id":"https://openalex.org/C9679016","wikidata":"https://www.wikidata.org/wiki/Q1417473","display_name":"Principle of maximum entropy","level":2,"score":0.29490000009536743},{"id":"https://openalex.org/C167981619","wikidata":"https://www.wikidata.org/wiki/Q1685498","display_name":"Cross entropy","level":3,"score":0.2922999858856201},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.2913999855518341},{"id":"https://openalex.org/C129848803","wikidata":"https://www.wikidata.org/wiki/Q2564360","display_name":"Sample size determination","level":2,"score":0.2736000120639801},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2635999917984009},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.262800008058548},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.2524999976158142},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.25220000743865967}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.07801","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.07801","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.07801","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.07801","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Sampling-based":[0],"model":[1,8],"predictive":[2,9],"control":[3,19],"(MPC)":[4],"algorithms,":[5],"such":[6,48],"as":[7,49],"path":[10],"integral":[11],"(MPPI),":[12],"enable":[13],"approximate,":[14],"gradient-free":[15],"solutions":[16],"to":[17],"optimal":[18,94],"problems":[20],"by":[21,106],"drawing":[22],"samples":[23],"from":[24],"a":[25,58,73],"proposal":[26,35,70],"distribution,":[27],"evaluating":[28],"their":[29],"trajectory":[30],"costs,":[31],"and":[32,104,134,140],"updating":[33],"the":[34,69,96,108,126],"parameters":[36],"accordingly.":[37],"However,":[38],"these":[39],"approaches":[40],"typically":[41],"rely":[42],"on":[43,120],"heuristics":[44],"for":[45,62],"adjusting":[46],"hyperparameters,":[47],"temperature":[50],"or":[51,53],"momentum,":[52],"manual":[54],"tuning.":[55],"We":[56,99],"propose":[57],"trust":[59,109,128],"region":[60,110,129],"formulation":[61],"sampling-based":[63],"MPC":[64],"that":[65,92,125],"constrains":[66],"updates":[67],"of":[68],"distribution":[71,116],"via":[72],"principled":[74],"Kullback--Leibler":[75],"(KL)":[76],"divergence":[77],"bound":[78],"and,":[79],"optionally,":[80],"an":[81],"entropy":[82],"lower":[83],"bound.":[84],"This":[85],"replaces":[86],"heuristic":[87],"hyperparameter":[88],"adaptation":[89],"with":[90,112,146],"values":[91],"are":[93],"w.r.t.":[95],"underlying":[97],"Lagrangian.":[98],"further":[100],"improve":[101],"sample":[102,136],"efficiency":[103,137],"convergence":[105,133],"combining":[107],"update":[111,130],"deterministic":[113,147],"localized":[114],"cumulative":[115],"(LCD)-based":[117],"sampling.":[118,149],"Experiments":[119],"two":[121],"benchmark":[122],"environments":[123],"demonstrate":[124],"proposed":[127],"achieves":[131],"faster":[132],"better":[135],"in":[138],"low-sample":[139],"low-iteration":[141],"regimes,":[142],"especially":[143],"when":[144],"paired":[145],"LCD-based":[148]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-05-12T00:00:00"}