{"id":"https://openalex.org/W2785396776","doi":"https://doi.org/10.1109/ssci.2017.8285204","title":"Model predictive PseudoSpectral Optimal Control with semi-parametric dynamics","display_name":"Model predictive PseudoSpectral Optimal Control with semi-parametric dynamics","publication_year":2017,"publication_date":"2017-11-01","ids":{"openalex":"https://openalex.org/W2785396776","doi":"https://doi.org/10.1109/ssci.2017.8285204","mag":"2785396776"},"language":"en","primary_location":{"id":"doi:10.1109/ssci.2017.8285204","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssci.2017.8285204","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE Symposium Series on Computational Intelligence (SSCI)","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/A5017948015","display_name":"Manan Gandhi","orcid":null},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Manan Gandhi","raw_affiliation_strings":["School of Aerospace Engineering, Georgia Institute of Technology"],"affiliations":[{"raw_affiliation_string":"School of Aerospace Engineering, Georgia Institute of Technology","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017764509","display_name":"Kamil Saigol","orcid":null},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kamil Saigol","raw_affiliation_strings":["Institute for Robotics and Intelligent Machines, Georgia Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Institute for Robotics and Intelligent Machines, Georgia Institute of Technology","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091291585","display_name":"Yunpeng Pan","orcid":"https://orcid.org/0000-0002-3373-0769"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yunpeng Pan","raw_affiliation_strings":["Institute for Robotics and Intelligent Machines, Georgia Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Institute for Robotics and Intelligent Machines, Georgia Institute of Technology","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044505993","display_name":"Evangelos A. Theodorou","orcid":"https://orcid.org/0000-0002-0834-5738"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Evangelos Theodorou","raw_affiliation_strings":["School of Aerospace Engineering, Georgia Institute of Technology"],"affiliations":[{"raw_affiliation_string":"School of Aerospace Engineering, Georgia Institute of Technology","institution_ids":["https://openalex.org/I130701444"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5017948015"],"corresponding_institution_ids":["https://openalex.org/I130701444"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1993576,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"70","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9993000030517578,"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"}},"topics":[{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9993000030517578,"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/T11236","display_name":"Control Systems and Identification","score":0.9828000068664551,"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/T10791","display_name":"Advanced Control Systems Optimization","score":0.9760000109672546,"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/gaussian-process","display_name":"Gaussian process","score":0.6880995035171509},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6348364949226379},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.632790207862854},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6229338645935059},{"id":"https://openalex.org/keywords/trajectory-optimization","display_name":"Trajectory optimization","score":0.5217662453651428},{"id":"https://openalex.org/keywords/pseudospectral-optimal-control","display_name":"Pseudospectral optimal control","score":0.5037927031517029},{"id":"https://openalex.org/keywords/optimal-control","display_name":"Optimal control","score":0.4843333959579468},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.468614399433136},{"id":"https://openalex.org/keywords/parametric-model","display_name":"Parametric model","score":0.4641820788383484},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44907432794570923},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.39325645565986633},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3701164722442627},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.3447904586791992},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18825548887252808},{"id":"https://openalex.org/keywords/pseudo-spectral-method","display_name":"Pseudo-spectral method","score":0.15439608693122864}],"concepts":[{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.6880995035171509},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6348364949226379},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.632790207862854},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6229338645935059},{"id":"https://openalex.org/C173246807","wikidata":"https://www.wikidata.org/wiki/Q7833062","display_name":"Trajectory optimization","level":3,"score":0.5217662453651428},{"id":"https://openalex.org/C154304650","wikidata":"https://www.wikidata.org/wiki/Q7255577","display_name":"Pseudospectral optimal control","level":5,"score":0.5037927031517029},{"id":"https://openalex.org/C91575142","wikidata":"https://www.wikidata.org/wiki/Q1971426","display_name":"Optimal control","level":2,"score":0.4843333959579468},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.468614399433136},{"id":"https://openalex.org/C24574437","wikidata":"https://www.wikidata.org/wiki/Q7135228","display_name":"Parametric model","level":3,"score":0.4641820788383484},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44907432794570923},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39325645565986633},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3701164722442627},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.3447904586791992},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18825548887252808},{"id":"https://openalex.org/C177937620","wikidata":"https://www.wikidata.org/wiki/Q7254447","display_name":"Pseudo-spectral method","level":4,"score":0.15439608693122864},{"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/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C203024314","wikidata":"https://www.wikidata.org/wiki/Q1365258","display_name":"Fourier analysis","level":3,"score":0.0},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.0},{"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/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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ssci.2017.8285204","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssci.2017.8285204","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE Symposium Series on Computational Intelligence (SSCI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1537311147","https://openalex.org/W1746819321","https://openalex.org/W1992244412","https://openalex.org/W1998179438","https://openalex.org/W2007864935","https://openalex.org/W2014903366","https://openalex.org/W2018705428","https://openalex.org/W2124609748","https://openalex.org/W2130527887","https://openalex.org/W2130913800","https://openalex.org/W2143346970","https://openalex.org/W2144902422","https://openalex.org/W2146611938","https://openalex.org/W2166063021","https://openalex.org/W2166684357","https://openalex.org/W2170912685","https://openalex.org/W2326578090","https://openalex.org/W2588422783","https://openalex.org/W2742077738","https://openalex.org/W2762483932","https://openalex.org/W4211049957","https://openalex.org/W4230031267","https://openalex.org/W6679524480","https://openalex.org/W6681302627","https://openalex.org/W6684451488","https://openalex.org/W6742417552"],"related_works":["https://openalex.org/W2285963647","https://openalex.org/W2103854823","https://openalex.org/W2372608005","https://openalex.org/W2141789111","https://openalex.org/W3005220537","https://openalex.org/W2032378738","https://openalex.org/W2063141165","https://openalex.org/W2359296948","https://openalex.org/W2247436960","https://openalex.org/W2375323942"],"abstract_inverted_index":{"Trajectory":[0],"optimization":[1,16,162],"of":[2,11,23,31,35,73,152],"a":[3,33,50,70,88,97,104],"controlled":[4],"dynamical":[5,51],"system":[6,76],"is":[7,80,155],"an":[8,121,135],"essential":[9],"part":[10],"autonomy,":[12],"however":[13],"many":[14],"trajectory":[15],"techniques":[17,44,163],"are":[18],"limited":[19],"by":[20,45,68],"the":[21,24,29,54,61,74,83,160],"fidelity":[22],"underlying":[25,75],"parametric":[26,131],"model.":[27],"In":[28,127],"field":[30],"robotics,":[32],"lack":[34],"model":[36,52,92,110,118],"knowledge":[37],"can":[38],"be":[39],"overcome":[40],"with":[41,96,111,164],"machine":[42],"learning":[43,119,146],"utilizing":[46],"measurements":[47],"to":[48,59,81,129,156],"build":[49],"from":[53],"data.":[55],"This":[56],"paper":[57,154],"aims":[58],"take":[60],"middle":[62],"ground":[63],"between":[64],"these":[65],"two":[66],"approaches":[67],"introducing":[69],"semi-parametric":[71,109,165],"representation":[72],"dynamics.":[77],"Our":[78],"goal":[79,151],"leverage":[82],"considerable":[84],"information":[85],"contained":[86],"in":[87,120],"traditional":[89],"physics":[90],"based":[91],"and":[93,123,158],"combine":[94],"it":[95],"data-driven,":[98],"non-parametric":[99],"regression":[100],"technique":[101],"known":[102],"as":[103],"Gaussian":[105,141],"Process.":[106],"Integrating":[107],"this":[108,153],"PseudoSpectral":[112],"Optimal":[113],"Control":[114],"(PSOC),":[115],"we":[116,133],"demonstrate":[117,159],"episodic":[122],"receding":[124],"horizon":[125],"fashion.":[126],"order":[128],"manage":[130],"uncertainty,":[132],"introduce":[134],"algorithm":[136],"that":[137],"utilizes":[138],"Sparse":[139],"Spectrum":[140],"Processes":[142],"(SSGP)":[143],"for":[144,167],"incremental":[145],"after":[147],"each":[148],"rollout.":[149],"The":[150],"motivate":[157],"constrained":[161],"models":[166],"online":[168],"learning.":[169]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}