{"id":"https://openalex.org/W4417002441","doi":"https://doi.org/10.1109/tits.2025.3632894","title":"Anti-Collision Near Optimal Enclosing Control for UAVs: A Fixed-Time Learning-Based ADP Solution","display_name":"Anti-Collision Near Optimal Enclosing Control for UAVs: A Fixed-Time Learning-Based ADP Solution","publication_year":2025,"publication_date":"2025-12-04","ids":{"openalex":"https://openalex.org/W4417002441","doi":"https://doi.org/10.1109/tits.2025.3632894"},"language":null,"primary_location":{"id":"doi:10.1109/tits.2025.3632894","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tits.2025.3632894","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1109/tits.2025.3632894","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100782837","display_name":"Xingling Shao","orcid":"https://orcid.org/0000-0002-6187-4575"},"institutions":[{"id":"https://openalex.org/I135714990","display_name":"North University of China","ror":"https://ror.org/047bp1713","country_code":"CN","type":"education","lineage":["https://openalex.org/I135714990"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xingling Shao","raw_affiliation_strings":["School of Electrical and Control Engineering, North University of China, Taiyuan, China"],"raw_orcid":"https://orcid.org/0000-0002-6187-4575","affiliations":[{"raw_affiliation_string":"School of Electrical and Control Engineering, North University of China, Taiyuan, China","institution_ids":["https://openalex.org/I135714990"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110590539","display_name":"Y. T. Cheng","orcid":"https://orcid.org/0009-0004-2357-3749"},"institutions":[{"id":"https://openalex.org/I135714990","display_name":"North University of China","ror":"https://ror.org/047bp1713","country_code":"CN","type":"education","lineage":["https://openalex.org/I135714990"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunjie Cheng","raw_affiliation_strings":["School of Instrument and Electronics, North University of China, Taiyuan, China"],"raw_orcid":"https://orcid.org/0009-0004-2357-3749","affiliations":[{"raw_affiliation_string":"School of Instrument and Electronics, North University of China, Taiyuan, China","institution_ids":["https://openalex.org/I135714990"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103835377","display_name":"Wanning Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I135714990","display_name":"North University of China","ror":"https://ror.org/047bp1713","country_code":"CN","type":"education","lineage":["https://openalex.org/I135714990"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wanning Wang","raw_affiliation_strings":["School of Instrument and Electronics, North University of China, Taiyuan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Instrument and Electronics, North University of China, Taiyuan, China","institution_ids":["https://openalex.org/I135714990"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100422653","display_name":"Hongyu Wang","orcid":"https://orcid.org/0000-0002-7710-4591"},"institutions":[{"id":"https://openalex.org/I135714990","display_name":"North University of China","ror":"https://ror.org/047bp1713","country_code":"CN","type":"education","lineage":["https://openalex.org/I135714990"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongyu Wang","raw_affiliation_strings":["School of Electrical and Control Engineering, North University of China, Taiyuan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical and Control Engineering, North University of China, Taiyuan, China","institution_ids":["https://openalex.org/I135714990"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jun Liu","orcid":"https://orcid.org/0000-0002-1128-8201"},"institutions":[{"id":"https://openalex.org/I135714990","display_name":"North University of China","ror":"https://ror.org/047bp1713","country_code":"CN","type":"education","lineage":["https://openalex.org/I135714990"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Liu","raw_affiliation_strings":["School of Instrument and Electronics, North University of China, Taiyuan, China"],"raw_orcid":"https://orcid.org/0000-0002-1128-8201","affiliations":[{"raw_affiliation_string":"School of Instrument and Electronics, North University of China, Taiyuan, China","institution_ids":["https://openalex.org/I135714990"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101820630","display_name":"Qingzhen Zhang","orcid":"https://orcid.org/0000-0002-7968-3523"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingzhen Zhang","raw_affiliation_strings":["School of Automation Science and Electrical Engineering, Beihang University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automation Science and Electrical Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.5929,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.8746315,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"27","issue":"2","first_page":"1773","last_page":"1786"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12794","display_name":"Adaptive Dynamic Programming Control","score":0.9733999967575073,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12794","display_name":"Adaptive Dynamic Programming Control","score":0.9733999967575073,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.006300000008195639,"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"}},{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.0010000000474974513,"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/control-theory","display_name":"Control theory (sociology)","score":0.7016000151634216},{"id":"https://openalex.org/keywords/optimal-control","display_name":"Optimal control","score":0.6657000184059143},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.5837000012397766},{"id":"https://openalex.org/keywords/dynamic-programming","display_name":"Dynamic programming","score":0.5770999789237976},{"id":"https://openalex.org/keywords/obstacle-avoidance","display_name":"Obstacle avoidance","score":0.5760999917984009},{"id":"https://openalex.org/keywords/obstacle","display_name":"Obstacle","score":0.5236999988555908},{"id":"https://openalex.org/keywords/feed-forward","display_name":"Feed forward","score":0.5004000067710876},{"id":"https://openalex.org/keywords/adaptive-control","display_name":"Adaptive control","score":0.49079999327659607},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.47200000286102295},{"id":"https://openalex.org/keywords/bellman-equation","display_name":"Bellman equation","score":0.4593000113964081}],"concepts":[{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.7016000151634216},{"id":"https://openalex.org/C91575142","wikidata":"https://www.wikidata.org/wiki/Q1971426","display_name":"Optimal control","level":2,"score":0.6657000184059143},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.5837000012397766},{"id":"https://openalex.org/C37404715","wikidata":"https://www.wikidata.org/wiki/Q380679","display_name":"Dynamic programming","level":2,"score":0.5770999789237976},{"id":"https://openalex.org/C6683253","wikidata":"https://www.wikidata.org/wiki/Q7075535","display_name":"Obstacle avoidance","level":4,"score":0.5760999917984009},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5299999713897705},{"id":"https://openalex.org/C2776650193","wikidata":"https://www.wikidata.org/wiki/Q264661","display_name":"Obstacle","level":2,"score":0.5236999988555908},{"id":"https://openalex.org/C38858127","wikidata":"https://www.wikidata.org/wiki/Q5441228","display_name":"Feed forward","level":2,"score":0.5004000067710876},{"id":"https://openalex.org/C107464732","wikidata":"https://www.wikidata.org/wiki/Q235781","display_name":"Adaptive control","level":3,"score":0.49079999327659607},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.47200000286102295},{"id":"https://openalex.org/C14646407","wikidata":"https://www.wikidata.org/wiki/Q1430750","display_name":"Bellman equation","level":2,"score":0.4593000113964081},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.4578999876976013},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.45500001311302185},{"id":"https://openalex.org/C2780799671","wikidata":"https://www.wikidata.org/wiki/Q17087362","display_name":"Transient (computer programming)","level":2,"score":0.453900009393692},{"id":"https://openalex.org/C79487989","wikidata":"https://www.wikidata.org/wiki/Q934680","display_name":"Vehicle dynamics","level":2,"score":0.4505999982357025},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.44200000166893005},{"id":"https://openalex.org/C2780864053","wikidata":"https://www.wikidata.org/wiki/Q5147495","display_name":"Collision avoidance","level":3,"score":0.44020000100135803},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.38760000467300415},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.38679999113082886},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.36719998717308044},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.36469998955726624},{"id":"https://openalex.org/C45882903","wikidata":"https://www.wikidata.org/wiki/Q5042317","display_name":"Fuel efficiency","level":2,"score":0.34470000863075256},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.3416000008583069},{"id":"https://openalex.org/C47702885","wikidata":"https://www.wikidata.org/wiki/Q5441227","display_name":"Feedforward neural network","level":3,"score":0.30140000581741333},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.289000004529953},{"id":"https://openalex.org/C17500928","wikidata":"https://www.wikidata.org/wiki/Q959968","display_name":"Control system","level":2,"score":0.27549999952316284},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.2750999927520752},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2680000066757202},{"id":"https://openalex.org/C2779127903","wikidata":"https://www.wikidata.org/wiki/Q6510194","display_name":"Learning rule","level":3,"score":0.2628999948501587},{"id":"https://openalex.org/C125014702","wikidata":"https://www.wikidata.org/wiki/Q4680749","display_name":"Adaptive learning","level":2,"score":0.259799987077713},{"id":"https://openalex.org/C85761212","wikidata":"https://www.wikidata.org/wiki/Q1974593","display_name":"Transient response","level":2,"score":0.2565000057220459},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.2547999918460846}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2025.3632894","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tits.2025.3632894","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1109/tits.2025.3632894","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tits.2025.3632894","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5770850125","display_name":null,"funder_award_id":"62173312","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8359344949","display_name":null,"funder_award_id":"202203021224008","funder_id":"https://openalex.org/F4320335445","funder_display_name":"Outstanding Youth Foundation of Jiangsu Province of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335445","display_name":"Outstanding Youth Foundation of Jiangsu Province of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"This":[0],"article":[1],"solves":[2],"an":[3,25,37,129],"anti-collision":[4],"near":[5],"optimal":[6,33,83],"enclosing":[7,161],"control":[8,95],"for":[9],"Uncrewed":[10],"Aerial":[11],"Vehicles":[12],"(UAVs)":[13],"under":[14,55,77],"a":[15,31,52,59,66,78,81,106,141,172],"fixed-time":[16,131],"learning":[17,132,175],"based":[18,123],"adaptive":[19,26,38],"dynamic":[20],"programming":[21],"(ADP)":[22],"context,":[23],"containing":[24],"feedforward":[27,39],"circling":[28,40],"item":[29,41],"and":[30,49,68,93,160,203],"collision-free":[32,82],"stabilization":[34,84],"policy.":[35],"First,":[36],"is":[42,62,86,116,138,156,178],"derived":[43],"to":[44,47,88,198],"steer":[45],"UAVs":[46],"approximate":[48],"evolve":[50],"along":[51],"desired":[53],"circle":[54],"wind":[56],"interferences.":[57],"Specifically,":[58],"neural":[60],"predictor":[61],"incorporated":[63],"that":[64,110,157,179],"enables":[65],"smooth":[67],"accurate":[69],"uncertainty":[70],"estimate":[71],"without":[72],"imposing":[73],"transient":[74],"chattering.":[75],"Next,":[76],"critic-only":[79],"ADP,":[80],"policy":[85],"developed":[87],"tackle":[89],"static":[90],"obstacle":[91,158],"avoidance":[92,159],"preserve":[94],"optimality":[96],"with":[97,167,189],"the":[98,112,119],"minimum":[99],"energy":[100,180],"cost.":[101],"To":[102],"achieve":[103],"collision":[104],"elimination,":[105],"novel":[107],"barrier":[108],"function":[109],"describes":[111],"hitting":[113],"risk":[114],"degree":[115],"augmented":[117],"in":[118,171],"value":[120],"function.":[121],"Especially,":[122],"on":[124],"integration":[125],"of":[126,205],"historical":[127],"data,":[128],"innovative":[130],"rule":[133],"driven":[134],"by":[135,185,210],"weight":[136,147,169],"errors":[137,194],"elaborated,":[139],"retaining":[140],"prescribed":[142],"convergence":[143],"free":[144],"from":[145],"initial":[146],"selections.":[148],"The":[149,201],"unique":[150],"innovation":[151],"includes":[152],"two":[153],"aspects,":[154],"one":[155],"maintenance":[162],"are":[163,195,208],"simultaneously":[164],"guaranteed":[165],"even":[166],"different":[168],"initializations":[170],"unified":[173],"ADP":[174],"paradigm,":[176],"another":[177],"consumption":[181],"can":[182],"be":[183,199],"reduced":[184],"approximately":[186],"18.9%":[187],"compared":[188],"artificial":[190],"potential":[191],"field.":[192],"Involved":[193],"theoretically":[196],"demonstrated":[197],"convergent.":[200],"usefulness":[202],"merits":[204],"presented":[206],"algorithm":[207],"accessed":[209],"abundant":[211],"comparisons.":[212]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-12-04T00:00:00"}