Risk-Bounded Control Using Stochastic Barrier Functions
In this letter, we design real-time controllers that react to uncertainties with stochastic characteristics and bound the probability of a failure in finite-time to a given desired value. Stochastic control barrier functions are used to derive sufficient conditions on the control input that bound th...
Gespeichert in:
| Veröffentlicht in: | IEEE control systems letters 2021-11, Vol.5 (5), p.1831-1836 |
|---|---|
| Hauptverfasser: | , , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext bestellen |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 1836 |
|---|---|
| container_issue | 5 |
| container_start_page | 1831 |
| container_title | IEEE control systems letters |
| container_volume | 5 |
| creator | Yaghoubi, Shakiba Majd, Keyvan Fainekos, Georgios Yamaguchi, Tomoya Prokhorov, Danil Hoxha, Bardh |
| description | In this letter, we design real-time controllers that react to uncertainties with stochastic characteristics and bound the probability of a failure in finite-time to a given desired value. Stochastic control barrier functions are used to derive sufficient conditions on the control input that bound the probability that the states of the system enter an unsafe region within a finite time. These conditions are combined with reachability conditions and used in an optimization problem to find the required control actions that lead the system to a goal set. We illustrate our theoretical development using a simulation of a lane-changing scenario in a highway with dense traffic. |
| doi_str_mv | 10.1109/LCSYS.2020.3043287 |
| format | Article |
| fullrecord | <record><control><sourceid>crossref_RIE</sourceid><recordid>TN_cdi_ieee_primary_9286497</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>9286497</ieee_id><sourcerecordid>10_1109_LCSYS_2020_3043287</sourcerecordid><originalsourceid>FETCH-LOGICAL-c311t-6443bb9ed7ce235d9be77891e55ea5ad3e577d0a4253ecf58a46e9b477879c4d3</originalsourceid><addsrcrecordid>eNpNj01OwzAYRC0EElXpBWCTCyT4N46XNKKAFAmJ0AUry7G_gKHEyHYX3J6WVojVzGLeSA-hS4IrQrC67tr-pa8oprhimDPayBM0o1yKknBRn_7r52iR0jvGmDRUYqpmSD759FEuw3Zy4Io2TDmGTbFOfnot-hzsm0nZ22JpYvQQi9V2stmHKV2gs9FsEiyOOUfr1e1ze192j3cP7U1XWkZILmvO2TAocNICZcKpAaRsFAEhwAjjGAgpHTacCgZ2FI3hNaiB70ZSWe7YHNHDr40hpQij_or-08RvTbDe2-tfe72310f7HXR1gDwA_AGKNjVXkv0ATbFWFA</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>Risk-Bounded Control Using Stochastic Barrier Functions</title><source>IEEE Electronic Library (IEL)</source><creator>Yaghoubi, Shakiba ; Majd, Keyvan ; Fainekos, Georgios ; Yamaguchi, Tomoya ; Prokhorov, Danil ; Hoxha, Bardh</creator><creatorcontrib>Yaghoubi, Shakiba ; Majd, Keyvan ; Fainekos, Georgios ; Yamaguchi, Tomoya ; Prokhorov, Danil ; Hoxha, Bardh</creatorcontrib><description>In this letter, we design real-time controllers that react to uncertainties with stochastic characteristics and bound the probability of a failure in finite-time to a given desired value. Stochastic control barrier functions are used to derive sufficient conditions on the control input that bound the probability that the states of the system enter an unsafe region within a finite time. These conditions are combined with reachability conditions and used in an optimization problem to find the required control actions that lead the system to a goal set. We illustrate our theoretical development using a simulation of a lane-changing scenario in a highway with dense traffic.</description><identifier>ISSN: 2475-1456</identifier><identifier>EISSN: 2475-1456</identifier><identifier>DOI: 10.1109/LCSYS.2020.3043287</identifier><identifier>CODEN: ICSLBO</identifier><language>eng</language><publisher>IEEE</publisher><subject>Barrier function ; Generators ; Planning ; Real-time systems ; robotics ; Safety ; Stochastic processes ; Stochastic systems ; Uncertainty</subject><ispartof>IEEE control systems letters, 2021-11, Vol.5 (5), p.1831-1836</ispartof><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c311t-6443bb9ed7ce235d9be77891e55ea5ad3e577d0a4253ecf58a46e9b477879c4d3</citedby><cites>FETCH-LOGICAL-c311t-6443bb9ed7ce235d9be77891e55ea5ad3e577d0a4253ecf58a46e9b477879c4d3</cites><orcidid>0000-0002-0456-2129 ; 0000-0002-6208-4233 ; 0000-0003-0996-5725 ; 0000-0001-6255-7566</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9286497$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27901,27902,54733</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/9286497$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Yaghoubi, Shakiba</creatorcontrib><creatorcontrib>Majd, Keyvan</creatorcontrib><creatorcontrib>Fainekos, Georgios</creatorcontrib><creatorcontrib>Yamaguchi, Tomoya</creatorcontrib><creatorcontrib>Prokhorov, Danil</creatorcontrib><creatorcontrib>Hoxha, Bardh</creatorcontrib><title>Risk-Bounded Control Using Stochastic Barrier Functions</title><title>IEEE control systems letters</title><addtitle>LCSYS</addtitle><description>In this letter, we design real-time controllers that react to uncertainties with stochastic characteristics and bound the probability of a failure in finite-time to a given desired value. Stochastic control barrier functions are used to derive sufficient conditions on the control input that bound the probability that the states of the system enter an unsafe region within a finite time. These conditions are combined with reachability conditions and used in an optimization problem to find the required control actions that lead the system to a goal set. We illustrate our theoretical development using a simulation of a lane-changing scenario in a highway with dense traffic.</description><subject>Barrier function</subject><subject>Generators</subject><subject>Planning</subject><subject>Real-time systems</subject><subject>robotics</subject><subject>Safety</subject><subject>Stochastic processes</subject><subject>Stochastic systems</subject><subject>Uncertainty</subject><issn>2475-1456</issn><issn>2475-1456</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpNj01OwzAYRC0EElXpBWCTCyT4N46XNKKAFAmJ0AUry7G_gKHEyHYX3J6WVojVzGLeSA-hS4IrQrC67tr-pa8oprhimDPayBM0o1yKknBRn_7r52iR0jvGmDRUYqpmSD759FEuw3Zy4Io2TDmGTbFOfnot-hzsm0nZ22JpYvQQi9V2stmHKV2gs9FsEiyOOUfr1e1ze192j3cP7U1XWkZILmvO2TAocNICZcKpAaRsFAEhwAjjGAgpHTacCgZ2FI3hNaiB70ZSWe7YHNHDr40hpQij_or-08RvTbDe2-tfe72310f7HXR1gDwA_AGKNjVXkv0ATbFWFA</recordid><startdate>202111</startdate><enddate>202111</enddate><creator>Yaghoubi, Shakiba</creator><creator>Majd, Keyvan</creator><creator>Fainekos, Georgios</creator><creator>Yamaguchi, Tomoya</creator><creator>Prokhorov, Danil</creator><creator>Hoxha, Bardh</creator><general>IEEE</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><orcidid>https://orcid.org/0000-0002-0456-2129</orcidid><orcidid>https://orcid.org/0000-0002-6208-4233</orcidid><orcidid>https://orcid.org/0000-0003-0996-5725</orcidid><orcidid>https://orcid.org/0000-0001-6255-7566</orcidid></search><sort><creationdate>202111</creationdate><title>Risk-Bounded Control Using Stochastic Barrier Functions</title><author>Yaghoubi, Shakiba ; Majd, Keyvan ; Fainekos, Georgios ; Yamaguchi, Tomoya ; Prokhorov, Danil ; Hoxha, Bardh</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c311t-6443bb9ed7ce235d9be77891e55ea5ad3e577d0a4253ecf58a46e9b477879c4d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Barrier function</topic><topic>Generators</topic><topic>Planning</topic><topic>Real-time systems</topic><topic>robotics</topic><topic>Safety</topic><topic>Stochastic processes</topic><topic>Stochastic systems</topic><topic>Uncertainty</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Yaghoubi, Shakiba</creatorcontrib><creatorcontrib>Majd, Keyvan</creatorcontrib><creatorcontrib>Fainekos, Georgios</creatorcontrib><creatorcontrib>Yamaguchi, Tomoya</creatorcontrib><creatorcontrib>Prokhorov, Danil</creatorcontrib><creatorcontrib>Hoxha, Bardh</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><jtitle>IEEE control systems letters</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Yaghoubi, Shakiba</au><au>Majd, Keyvan</au><au>Fainekos, Georgios</au><au>Yamaguchi, Tomoya</au><au>Prokhorov, Danil</au><au>Hoxha, Bardh</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Risk-Bounded Control Using Stochastic Barrier Functions</atitle><jtitle>IEEE control systems letters</jtitle><stitle>LCSYS</stitle><date>2021-11</date><risdate>2021</risdate><volume>5</volume><issue>5</issue><spage>1831</spage><epage>1836</epage><pages>1831-1836</pages><issn>2475-1456</issn><eissn>2475-1456</eissn><coden>ICSLBO</coden><abstract>In this letter, we design real-time controllers that react to uncertainties with stochastic characteristics and bound the probability of a failure in finite-time to a given desired value. Stochastic control barrier functions are used to derive sufficient conditions on the control input that bound the probability that the states of the system enter an unsafe region within a finite time. These conditions are combined with reachability conditions and used in an optimization problem to find the required control actions that lead the system to a goal set. We illustrate our theoretical development using a simulation of a lane-changing scenario in a highway with dense traffic.</abstract><pub>IEEE</pub><doi>10.1109/LCSYS.2020.3043287</doi><tpages>6</tpages><orcidid>https://orcid.org/0000-0002-0456-2129</orcidid><orcidid>https://orcid.org/0000-0002-6208-4233</orcidid><orcidid>https://orcid.org/0000-0003-0996-5725</orcidid><orcidid>https://orcid.org/0000-0001-6255-7566</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | ISSN: 2475-1456 |
| ispartof | IEEE control systems letters, 2021-11, Vol.5 (5), p.1831-1836 |
| issn | 2475-1456 2475-1456 |
| language | eng |
| recordid | cdi_ieee_primary_9286497 |
| source | IEEE Electronic Library (IEL) |
| subjects | Barrier function Generators Planning Real-time systems robotics Safety Stochastic processes Stochastic systems Uncertainty |
| title | Risk-Bounded Control Using Stochastic Barrier Functions |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-05T07%3A57%3A54IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-crossref_RIE&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Risk-Bounded%20Control%20Using%20Stochastic%20Barrier%20Functions&rft.jtitle=IEEE%20control%20systems%20letters&rft.au=Yaghoubi,%20Shakiba&rft.date=2021-11&rft.volume=5&rft.issue=5&rft.spage=1831&rft.epage=1836&rft.pages=1831-1836&rft.issn=2475-1456&rft.eissn=2475-1456&rft.coden=ICSLBO&rft_id=info:doi/10.1109/LCSYS.2020.3043287&rft_dat=%3Ccrossref_RIE%3E10_1109_LCSYS_2020_3043287%3C/crossref_RIE%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=9286497&rfr_iscdi=true |