{"id":"https://openalex.org/W2923314748","doi":"https://doi.org/10.1109/cdc40024.2019.9029993","title":"Nonlinear Uncertainty Control with Iterative Covariance Steering","display_name":"Nonlinear Uncertainty Control with Iterative Covariance Steering","publication_year":2019,"publication_date":"2019-12-01","ids":{"openalex":"https://openalex.org/W2923314748","doi":"https://doi.org/10.1109/cdc40024.2019.9029993","mag":"2923314748"},"language":"en","primary_location":{"id":"doi:10.1109/cdc40024.2019.9029993","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cdc40024.2019.9029993","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 58th Conference on Decision and Control (CDC)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1903.10919","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5021471689","display_name":"Jack Ridderhof","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":"Jack Ridderhof","raw_affiliation_strings":["School of Aerospace Engineering, Georgia Institute of Technology, Atlanta, GA, USA","#N#\u2021#N#Georgia Institute of Technology#N#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Aerospace Engineering, Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]},{"raw_affiliation_string":"#N#\u2021#N#Georgia Institute of Technology#N#","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000307667","display_name":"Kazuhide Okamoto","orcid":"https://orcid.org/0000-0003-4222-8356"},"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":"Kazuhide Okamoto","raw_affiliation_strings":["School of Aerospace Engineering, Georgia Institute of Technology, Atlanta, GA, USA","#N#\u2021#N#Georgia Institute of Technology#N#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Aerospace Engineering, Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]},{"raw_affiliation_string":"#N#\u2021#N#Georgia Institute of Technology#N#","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077667229","display_name":"Panagiotis Tsiotras","orcid":"https://orcid.org/0000-0001-7563-4129"},"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":"Panagiotis Tsiotras","raw_affiliation_strings":["D. Guggenheim School of Aerospace Engineering and the Institute for Robotics and Intelligent Machines, Georgia Institute of Technology, Atlanta, GA, USA","#N#\u2021#N#Georgia Institute of Technology#N#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"D. Guggenheim School of Aerospace Engineering and the Institute for Robotics and Intelligent Machines, Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]},{"raw_affiliation_string":"#N#\u2021#N#Georgia Institute of Technology#N#","institution_ids":["https://openalex.org/I130701444"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I130701444"],"apc_list":null,"apc_paid":null,"fwci":0.1675,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.45184396,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"3484","last_page":"3490"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10791","display_name":"Advanced Control Systems Optimization","score":0.994700014591217,"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":0.994700014591217,"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":0.9732999801635742,"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/T10067","display_name":"Stochastic processes and financial applications","score":0.9656999707221985,"subfield":{"id":"https://openalex.org/subfields/2003","display_name":"Finance"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.7537926435470581},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.5964056253433228},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.5558614134788513},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.55540531873703},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5291091799736023},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.49555861949920654},{"id":"https://openalex.org/keywords/covariance-function","display_name":"Covariance function","score":0.4487277567386627},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.43496212363243103},{"id":"https://openalex.org/keywords/stochastic-control","display_name":"Stochastic control","score":0.41808682680130005},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.414631724357605},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3914252519607544},{"id":"https://openalex.org/keywords/optimal-control","display_name":"Optimal control","score":0.316023051738739},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.15443727374076843}],"concepts":[{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.7537926435470581},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5964056253433228},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.5558614134788513},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.55540531873703},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5291091799736023},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.49555861949920654},{"id":"https://openalex.org/C137250428","wikidata":"https://www.wikidata.org/wiki/Q5178897","display_name":"Covariance function","level":3,"score":0.4487277567386627},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.43496212363243103},{"id":"https://openalex.org/C170131372","wikidata":"https://www.wikidata.org/wiki/Q7617811","display_name":"Stochastic control","level":3,"score":0.41808682680130005},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.414631724357605},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3914252519607544},{"id":"https://openalex.org/C91575142","wikidata":"https://www.wikidata.org/wiki/Q1971426","display_name":"Optimal control","level":2,"score":0.316023051738739},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.15443727374076843},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"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/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/cdc40024.2019.9029993","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cdc40024.2019.9029993","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 58th Conference on Decision and Control (CDC)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1903.10919","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1903.10919","pdf_url":"https://arxiv.org/pdf/1903.10919","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":null},{"id":"mag:2923314748","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1903.10919","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1903.10919","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1903.10919","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1903.10919","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1903.10919","pdf_url":"https://arxiv.org/pdf/1903.10919","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":null},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5157548437","display_name":null,"funder_award_id":"CPS-1544814","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5689227516","display_name":"ENTRY  DESCENT  AND LANDING (EDL) IS THE PROCESS OF A SPACECRAFT ENTERING A PLANET'S ATMOSPHERE  DECELERATING FROM ORBIT  AND DESCENDING TO A SAFE LANDING ON THE PLANET'S SURFACE. EXTREME HEAT  HIGH AERODYNAMIC LOADS  DIFFICULTIES IN COMMUNICATION AND LOCALIZATION  AND SMALL GUIDANCE MARGINS CHARACTERIZE EDL. NASA TECHNOLOGY AREA (TA) 9.2.6 (LARGE DIVERT GUIDANCE) IDENTIFIES A GUARANTEE ON SATISFACTION OF CONSTRAINTS  OPTIMAL OR NEAR-OPTIMAL FUEL CONSUMPTION  AND ON-BOARD COMPUTATIONAL FEASIBILITY AS NECESSARY COMPONENTS OF A NEXT GENERATION SOLUTION. TO DATE  THE MOST ACCURATE EDL PROCEDURE WAS PERFORMED ON THE MSL MISSION WITH A LANDING TARGET ELLIPSE OF 10 KM WHILE TECHNOLOGY REQUIREMENTS (TA 9.2.6) CALL OUT A LANDING ELLIPSE REQUIREMENT ON THE ORDER OF 1 KM. STATE-OF-THE-ART DESCENT GUIDANCE METHODS RELY ON DETERMINISTIC FORMULATIONS OF SPACECRAFT DYNAMICS  AND HENCE ANY STATEMENT OF FUELCONSUMPTION OPTIMALITY CAN ONLY BE MADE WITH RESPECT TO A DETERMINISTIC MODEL. SINCE THERE EXIST UNMODELED DISTURBANCES IN PRACTICAL APPLICATION  WE CANNOT MAKE STRONG STATEMENTS REGARDING OPTIMALITY WHEN APPLYING DETERMINISTIC CONTROLLERS IN REAL SCENARIOS. FOR A CERTAIN CLASS OF SYSTEMS  CONTROLLERS DESIGNED USING STOCHASTIC OPTIMAL CONTROL THEORY HAVE BEEN SHOWN TO OUTPERFORM CLASSICAL CONTROLLERS. FURTHERMORE  RECENT DEVELOPMENTS IN STOCHASTIC OPTIMAL CONTROL THEORY HAVE SHOWN THAT LINEAR TIME-VARYING SYSTEMS WITH WEINER PROCESS NOISE CAN BE STEERED FROM INITIAL TO FINAL STATE MEAN AND COVARIANCE. WHILE NOT YET EXTENDED TO EDL  THESE DEVELOPMENTS IN STOCHASTIC OPTIMAL CONTROL THEORY MAY BE RELEVANT TO CONSTRUCTION OF BETTER PERFORMING DESCENT GUIDANCE SYSTEMS. THIS PROPOSED RESEARCH WILL CONSTITUTE AN ANALYSIS OF STOCHASTIC PROCESS THEORY AS APPLIED TO THE DESCENT GUIDANCE PROBLEM  WITH THE EXPECTATION OF IMPROVED FUEL PERFORMANCE. ADDITIONALLY  STOCHASTIC METHODS PROVIDE EXPLICIT DEFINITION OF STATE COVARIANCE  HENCE ALLOWING A SYSTEM DESIGNER TO CONSIDER TRADES OF COVARIANCE BOUNDS ON FUEL COST  POTENTIALLY LEADING TO IMPROVED SYSTEM PERFORMANCE. EXPECTED PRODUCTS OF THIS RESEARCH WILL INCLUDE PUBLICATIONS INTRODUCING EXTENSIONS TO STOCHASTIC CONTROL THEORY FOR CASES RELEVANT TO POWERED DESCENT GUIDANCE. THIS WORK WILL ALSO PRODUCE SIMULATION RESULTS COMPARING PERFORMANCE OF DETERMINISTIC AND STOCHASTIC CONTROLLERS.","funder_award_id":"80NSSC17K0093","funder_id":"https://openalex.org/F4320306101","funder_display_name":"National Aeronautics and Space Administration"},{"id":"https://openalex.org/G882470546","display_name":"CPS: Synergy: Collaborative Research: Adaptive Intelligence for Cyber-Physical Automotive Active Safety - System Design and Evaluation","funder_award_id":"1544814","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320306101","display_name":"National Aeronautics and Space Administration","ror":"https://ror.org/027ka1x80"},{"id":"https://openalex.org/F4320322037","display_name":"Nuclear Safety and Security Commission","ror":"https://ror.org/05qk3ge34"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2923314748.pdf","grobid_xml":"https://content.openalex.org/works/W2923314748.grobid-xml"},"referenced_works_count":31,"referenced_works":["https://openalex.org/W609616464","https://openalex.org/W1567262822","https://openalex.org/W1858982327","https://openalex.org/W1965842330","https://openalex.org/W1987420866","https://openalex.org/W2056257343","https://openalex.org/W2066557929","https://openalex.org/W2067778155","https://openalex.org/W2099506495","https://openalex.org/W2127788848","https://openalex.org/W2132004142","https://openalex.org/W2138693458","https://openalex.org/W2167856595","https://openalex.org/W2320211399","https://openalex.org/W2513178932","https://openalex.org/W2588273742","https://openalex.org/W2782371569","https://openalex.org/W2782427500","https://openalex.org/W2908954485","https://openalex.org/W2951559786","https://openalex.org/W2963293783","https://openalex.org/W2963859747","https://openalex.org/W2964076623","https://openalex.org/W2964187703","https://openalex.org/W3100727880","https://openalex.org/W3102244603","https://openalex.org/W4245164763","https://openalex.org/W4302609762","https://openalex.org/W6618825792","https://openalex.org/W6679445762","https://openalex.org/W6680368953"],"related_works":["https://openalex.org/W3011860312","https://openalex.org/W3139988784","https://openalex.org/W3127818199","https://openalex.org/W2099370259","https://openalex.org/W1975447466","https://openalex.org/W1990696058","https://openalex.org/W3108245990","https://openalex.org/W2996524046","https://openalex.org/W2117829448","https://openalex.org/W2126116278","https://openalex.org/W3154887018","https://openalex.org/W1996810588","https://openalex.org/W1640963076","https://openalex.org/W1536651105","https://openalex.org/W2053368412","https://openalex.org/W1517950598","https://openalex.org/W2974553480","https://openalex.org/W2056677059","https://openalex.org/W1989330774","https://openalex.org/W2611310856"],"abstract_inverted_index":{"This":[0,53],"paper":[1],"considers":[2],"the":[3,7],"problem":[4,41,48],"of":[5,10],"steering":[6,60],"state":[8],"distribution":[9,22],"a":[11,20,24,50,67],"nonlinear":[12],"stochastic":[13],"system":[14],"from":[15],"an":[16,45],"initial":[17],"Gaussian":[18],"to":[19,30,38,75],"terminal":[21],"with":[23,70],"specified":[25],"mean":[26],"and":[27],"covariance,":[28],"subject":[29,74],"probabilistic":[31,81],"path":[32,82],"constraints.":[33,83],"An":[34],"algorithm":[35],"is":[36,62],"developed":[37],"solve":[39],"this":[40],"by":[42,65],"iteratively":[43],"solving":[44],"approximate":[46],"linearized":[47],"as":[49],"convex":[51],"program.":[52],"method,":[54],"which":[55],"we":[56],"call":[57],"iterative":[58],"covariance":[59],"(iCS),":[61],"numerically":[63],"demonstrated":[64],"controlling":[66],"double":[68],"integrator":[69],"quadratic":[71],"drag":[72],"force":[73],"additive":[76],"Brownian":[77],"noise":[78],"while":[79],"satisfying":[80]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-01T08:55:40.977307","created_date":"2025-10-10T00:00:00"}
