{"id":"https://openalex.org/W4408182792","doi":"https://doi.org/10.1109/tcst.2025.3539218","title":"Empowering Autonomous Underwater Vehicles Using Learning-Based Model Predictive Control With Dynamic Forgetting Gaussian Processes","display_name":"Empowering Autonomous Underwater Vehicles Using Learning-Based Model Predictive Control With Dynamic Forgetting Gaussian Processes","publication_year":2025,"publication_date":"2025-03-06","ids":{"openalex":"https://openalex.org/W4408182792","doi":"https://doi.org/10.1109/tcst.2025.3539218"},"language":"en","primary_location":{"id":"doi:10.1109/tcst.2025.3539218","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcst.2025.3539218","pdf_url":null,"source":{"id":"https://openalex.org/S133363738","display_name":"IEEE Transactions on Control Systems Technology","issn_l":"1063-6536","issn":["1063-6536","1558-0865","2374-0159"],"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 Transactions on Control Systems Technology","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/A5002493765","display_name":"A. Amer","orcid":"https://orcid.org/0000-0001-5387-7613"},"institutions":[{"id":"https://openalex.org/I204337017","display_name":"Aarhus University","ror":"https://ror.org/01aj84f44","country_code":"DK","type":"education","lineage":["https://openalex.org/I204337017"]}],"countries":["DK"],"is_corresponding":true,"raw_author_name":"Abdelhakim Amer","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Artificial Intelligence in Robotics Laboratory (AiR Lab), Aarhus University, Aarhus, Denmark"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Artificial Intelligence in Robotics Laboratory (AiR Lab), Aarhus University, Aarhus, Denmark","institution_ids":["https://openalex.org/I204337017"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055769844","display_name":"Mohit Mehndiratta","orcid":"https://orcid.org/0000-0003-1958-0263"},"institutions":[{"id":"https://openalex.org/I4210096738","display_name":"Visual Components (Finland)","ror":"https://ror.org/00v7esy82","country_code":"FI","type":"company","lineage":["https://openalex.org/I4210096738"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Mohit Mehndiratta","raw_affiliation_strings":["GIM Robotics, Espoo, Finland"],"affiliations":[{"raw_affiliation_string":"GIM Robotics, Espoo, Finland","institution_ids":["https://openalex.org/I4210096738"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027959078","display_name":"Yury Brodskiy","orcid":"https://orcid.org/0009-0002-0445-8126"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yury Brodskiy","raw_affiliation_strings":["EIVA a/s, Skanderborg, Denmark"],"affiliations":[{"raw_affiliation_string":"EIVA a/s, Skanderborg, Denmark","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068099488","display_name":"Erdal Kayacan","orcid":"https://orcid.org/0000-0002-7143-8777"},"institutions":[{"id":"https://openalex.org/I206945453","display_name":"Paderborn University","ror":"https://ror.org/058kzsd48","country_code":"DE","type":"education","lineage":["https://openalex.org/I206945453"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Erdal Kayacan","raw_affiliation_strings":["Department of Electrical Engineering and Information Technology, Automatic Control Group (RAT), Paderborn University, Paderborn, Germany"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Information Technology, Automatic Control Group (RAT), Paderborn University, Paderborn, Germany","institution_ids":["https://openalex.org/I206945453"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5002493765"],"corresponding_institution_ids":["https://openalex.org/I204337017"],"apc_list":null,"apc_paid":null,"fwci":3.4851,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.91338583,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"33","issue":"5","first_page":"1913","last_page":"1920"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10791","display_name":"Advanced Control Systems Optimization","score":0.9254999756813049,"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":0.9254999756813049,"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":0.9104999899864197,"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/forgetting","display_name":"Forgetting","score":0.7999398708343506},{"id":"https://openalex.org/keywords/model-predictive-control","display_name":"Model predictive control","score":0.7389371991157532},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5303056240081787},{"id":"https://openalex.org/keywords/underwater","display_name":"Underwater","score":0.5013837814331055},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.4348088502883911},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4176332950592041},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.37760433554649353},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.33516359329223633},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3274746537208557},{"id":"https://openalex.org/keywords/control-engineering","display_name":"Control engineering","score":0.3237689733505249},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2400127351284027},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.14343759417533875},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.08551269769668579},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.06931501626968384},{"id":"https://openalex.org/keywords/cognitive-psychology","display_name":"Cognitive psychology","score":0.06836652755737305}],"concepts":[{"id":"https://openalex.org/C7149132","wikidata":"https://www.wikidata.org/wiki/Q1377840","display_name":"Forgetting","level":2,"score":0.7999398708343506},{"id":"https://openalex.org/C172205157","wikidata":"https://www.wikidata.org/wiki/Q1782962","display_name":"Model predictive control","level":3,"score":0.7389371991157532},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5303056240081787},{"id":"https://openalex.org/C98083399","wikidata":"https://www.wikidata.org/wiki/Q3246517","display_name":"Underwater","level":2,"score":0.5013837814331055},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.4348088502883911},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4176332950592041},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.37760433554649353},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.33516359329223633},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3274746537208557},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.3237689733505249},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2400127351284027},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.14343759417533875},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.08551269769668579},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.06931501626968384},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.06836652755737305},{"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/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tcst.2025.3539218","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcst.2025.3539218","pdf_url":null,"source":{"id":"https://openalex.org/S133363738","display_name":"IEEE Transactions on Control Systems Technology","issn_l":"1063-6536","issn":["1063-6536","1558-0865","2374-0159"],"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 Transactions on Control Systems Technology","raw_type":"journal-article"},{"id":"pmh:oai:pure.atira.dk:publications/89567dad-72c8-4a9b-9968-4d6f39bccc04","is_oa":false,"landing_page_url":"https://pure.au.dk/portal/en/publications/89567dad-72c8-4a9b-9968-4d6f39bccc04","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Amer, A H K S A, Mehndiratta, M, Brodskiy, Y & Kayacan, E 2025, 'Empowering Autonomous Underwater Vehicles Using Learning-Based Model Predictive Control With Dynamic Forgetting Gaussian Processes', IEEE Transactions on Control Systems Technology, vol. 33, no. 5, pp. 1913-1920. https://doi.org/10.1109/TCST.2025.3539218","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life below water","id":"https://metadata.un.org/sdg/14","score":0.6299999952316284}],"awards":[{"id":"https://openalex.org/G3698309722","display_name":null,"funder_award_id":"2040-00032B","funder_id":"https://openalex.org/F4320334111","funder_display_name":"Innovation Fund"},{"id":"https://openalex.org/G7063256467","display_name":null,"funder_award_id":"2040-00032B","funder_id":"https://openalex.org/F4320313796","funder_display_name":"Innovationsfonden"}],"funders":[{"id":"https://openalex.org/F4320313796","display_name":"Innovationsfonden","ror":"https://ror.org/00daj4111"},{"id":"https://openalex.org/F4320334111","display_name":"Innovation Fund","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1977164425","https://openalex.org/W2007864935","https://openalex.org/W2013439434","https://openalex.org/W2418467170","https://openalex.org/W2492811885","https://openalex.org/W2605255410","https://openalex.org/W2606358137","https://openalex.org/W2619551236","https://openalex.org/W2792969186","https://openalex.org/W2842089854","https://openalex.org/W2885836636","https://openalex.org/W2910288398","https://openalex.org/W2978951642","https://openalex.org/W3046286493","https://openalex.org/W3119715644","https://openalex.org/W3131850807","https://openalex.org/W3208270651","https://openalex.org/W4221033586","https://openalex.org/W4229014698","https://openalex.org/W4294691749","https://openalex.org/W4321380998","https://openalex.org/W4382935741","https://openalex.org/W4384819682","https://openalex.org/W4388676574","https://openalex.org/W4389667672","https://openalex.org/W4391422864","https://openalex.org/W4391423841","https://openalex.org/W4392567285","https://openalex.org/W6861242908"],"related_works":["https://openalex.org/W4289718052","https://openalex.org/W2164121020","https://openalex.org/W2145559838","https://openalex.org/W2905319430","https://openalex.org/W3116498279","https://openalex.org/W4287549553","https://openalex.org/W4310285384","https://openalex.org/W1964286703","https://openalex.org/W2169866437","https://openalex.org/W3056417032"],"abstract_inverted_index":{"Autonomous":[0],"underwater":[1,149],"vehicles":[2],"(AUVs)":[3],"present":[4],"several":[5],"challenges":[6],"due":[7],"to":[8,21],"the":[9,54,67,97,104,109,128,132,157,162,179],"complex":[10],"and":[11,30,153,159,174],"simultaneous":[12],"interplay":[13],"of":[14,111,122,161],"various":[15],"factors,":[16,117],"including":[17],"but":[18],"not":[19],"limited":[20],"unmodeled":[22],"dynamics,":[23],"highly":[24],"nonlinear":[25],"behavior,":[26],"intercouplings,":[27],"communication":[28],"delays,":[29],"environmental":[31,35],"disturbances.":[32],"In":[33,102],"particular,":[34],"disturbances":[36,62,130],"degrade":[37],"trajectory":[38],"tracking":[39,145,175],"performance":[40,146],"for":[41,92,99],"model-based":[42],"controllers,":[43],"e.g.,":[44],"model":[45,133],"predictive":[46],"control":[47,140],"(MPC)":[48],"algorithms.":[49],"Data-driven":[50],"methods":[51],"such":[52],"as":[53],"Gaussian":[55],"process":[56,72],"(GP)":[57],"are":[58],"effective":[59],"at":[60],"learning":[61],"in":[63,135,147,171],"real":[64],"time;":[65],"however,":[66],"underlying":[68],"offline":[69],"hyperparameter":[70,100],"tuning":[71],"limits":[73],"their":[74],"overall":[75],"effectiveness.":[76],"To":[77],"overcome":[78],"this":[79],"limitation,":[80],"we":[81],"propose":[82],"a":[83,138,168],"novel":[84],"dynamic":[85],"forgetting":[86,116],"GP":[87],"(DF-GP)":[88],"methodology":[89],"that":[90,142,178],"compensates":[91],"operational":[93],"disturbances,":[94],"thus":[95],"circumventing":[96],"need":[98],"retuning.":[101],"essence,":[103],"proposed":[105,163,180],"method":[106],"optimally":[107],"combines":[108],"predictions":[110],"individual":[112],"GPs\u2014designed":[113],"with":[114],"handcrafted":[115],"rendering":[118],"precise":[119],"disturbance":[120,172],"estimation":[121,173],"varying":[123],"timescales.":[124],"What":[125],"is":[126],"more,":[127],"predicted":[129],"update":[131],"parameters":[134],"MPC,":[136],"facilitating":[137],"learning-based":[139],"framework":[141,181],"ensures":[143],"accurate":[144],"different":[148],"scenarios.":[150],"Rigorous":[151],"simulation":[152],"real-world":[154],"experiments":[155],"demonstrate":[156],"efficiency":[158],"efficacy":[160],"framework.":[164],"The":[165],"results":[166],"show":[167],"25%":[169],"improvement":[170],"performance,":[176],"demonstrating":[177],"outperforms":[182],"its":[183],"direct":[184],"competitors.":[185]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}
