Random-Time, State-Dependent Stochastic Drift for Markov Chains and Application to Stochastic Stabilization Over Erasure Channels

It is known that state-dependent, multi-step Lyapunov bounds lead to greatly simplified verification theorems for stability for large classes of Markov chain models. This is one component of the "fluid model" approach to stability of stochastic networks. In this paper we extend the general...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on automatic control 2013-01, Vol.58 (1), p.47-59
Hauptverfasser: Yuksel, S., Meyn, S. P.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 59
container_issue 1
container_start_page 47
container_title IEEE transactions on automatic control
container_volume 58
creator Yuksel, S.
Meyn, S. P.
description It is known that state-dependent, multi-step Lyapunov bounds lead to greatly simplified verification theorems for stability for large classes of Markov chain models. This is one component of the "fluid model" approach to stability of stochastic networks. In this paper we extend the general theory to randomized multi-step Lyapunov theory to obtain criteria for stability and steady-state performance bounds, such as finite moments. These results are applied to a remote stabilization problem, in which a controller receives measurements from an erasure channel with limited capacity. Based on the general results in the paper it is shown that stability of the closed loop system is assured provided that the channel capacity is greater than the logarithm of the unstable eigenvalue, plus an additional correction term. The existence of a finite second moment in steady-state is established under additional conditions.
doi_str_mv 10.1109/TAC.2012.2204157
format Article
fullrecord <record><control><sourceid>proquest_RIE</sourceid><recordid>TN_cdi_crossref_primary_10_1109_TAC_2012_2204157</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>6215023</ieee_id><sourcerecordid>1283647247</sourcerecordid><originalsourceid>FETCH-LOGICAL-c366t-dc687755f00fc09b3409ddf8a8bce733d3bb88754c88aa2c24c7c85bbb30fc93</originalsourceid><addsrcrecordid>eNpdkU1LJDEQhoOs4Kx6F7wE9uLBHvPZSR-H8WMXFEHn3qTT1RjtSdokI6w3_7kZRpbFU_FSz1MUvAidUDKnlDQXq8Vyzghlc8aIoFLtoRmVUldMMv4DzQihumqYrg_Qz5SeS6yFoDP08WB8H9bVyq3hHD9mk6G6hAl8Dz6XHOyTSdlZfBndkPEQIr4z8SW84eWTcT7houPFNI3OmuyCxzn8b5WDnRvd-253_wYRX0WTNhG2vvcwpiO0P5gxwfHXPESr66vV8nd1e3_zZ7m4rSyv61z1ttZKSTkQMljSdFyQpu8HbXRnQXHe867TWklhtTaGWSasslp2XceL0PBDdLY7O8XwuoGU27VLFsbReAib1FKmeS0UE6qgv76hz2ETfXmuUEJIqZQihSI7ysaQUoShnaJbm_i3paTdVtKWStptJe1XJUU53SkOAP7hNaOSMM4_AXNLiJE</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1244557770</pqid></control><display><type>article</type><title>Random-Time, State-Dependent Stochastic Drift for Markov Chains and Application to Stochastic Stabilization Over Erasure Channels</title><source>IEEE Electronic Library (IEL)</source><creator>Yuksel, S. ; Meyn, S. P.</creator><creatorcontrib>Yuksel, S. ; Meyn, S. P.</creatorcontrib><description>It is known that state-dependent, multi-step Lyapunov bounds lead to greatly simplified verification theorems for stability for large classes of Markov chain models. This is one component of the "fluid model" approach to stability of stochastic networks. In this paper we extend the general theory to randomized multi-step Lyapunov theory to obtain criteria for stability and steady-state performance bounds, such as finite moments. These results are applied to a remote stabilization problem, in which a controller receives measurements from an erasure channel with limited capacity. Based on the general results in the paper it is shown that stability of the closed loop system is assured provided that the channel capacity is greater than the logarithm of the unstable eigenvalue, plus an additional correction term. The existence of a finite second moment in steady-state is established under additional conditions.</description><identifier>ISSN: 0018-9286</identifier><identifier>EISSN: 1558-2523</identifier><identifier>DOI: 10.1109/TAC.2012.2204157</identifier><identifier>CODEN: IETAA9</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Algorithms ; Asymptotic stability ; Channels ; Computational fluid dynamics ; Eigenvalues ; Information theory ; Markov chain Monte-Carlo (MCMC) ; Markov chains ; Markov processes ; Mathematical analysis ; networked control systems ; Noise ; Stability ; Stability criteria ; Stabilization ; Steady-state ; stochastic stability ; Stochasticity ; Studies</subject><ispartof>IEEE transactions on automatic control, 2013-01, Vol.58 (1), p.47-59</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Jan 2013</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c366t-dc687755f00fc09b3409ddf8a8bce733d3bb88754c88aa2c24c7c85bbb30fc93</citedby><cites>FETCH-LOGICAL-c366t-dc687755f00fc09b3409ddf8a8bce733d3bb88754c88aa2c24c7c85bbb30fc93</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/6215023$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,796,27924,27925,54758</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/6215023$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Yuksel, S.</creatorcontrib><creatorcontrib>Meyn, S. P.</creatorcontrib><title>Random-Time, State-Dependent Stochastic Drift for Markov Chains and Application to Stochastic Stabilization Over Erasure Channels</title><title>IEEE transactions on automatic control</title><addtitle>TAC</addtitle><description>It is known that state-dependent, multi-step Lyapunov bounds lead to greatly simplified verification theorems for stability for large classes of Markov chain models. This is one component of the "fluid model" approach to stability of stochastic networks. In this paper we extend the general theory to randomized multi-step Lyapunov theory to obtain criteria for stability and steady-state performance bounds, such as finite moments. These results are applied to a remote stabilization problem, in which a controller receives measurements from an erasure channel with limited capacity. Based on the general results in the paper it is shown that stability of the closed loop system is assured provided that the channel capacity is greater than the logarithm of the unstable eigenvalue, plus an additional correction term. The existence of a finite second moment in steady-state is established under additional conditions.</description><subject>Algorithms</subject><subject>Asymptotic stability</subject><subject>Channels</subject><subject>Computational fluid dynamics</subject><subject>Eigenvalues</subject><subject>Information theory</subject><subject>Markov chain Monte-Carlo (MCMC)</subject><subject>Markov chains</subject><subject>Markov processes</subject><subject>Mathematical analysis</subject><subject>networked control systems</subject><subject>Noise</subject><subject>Stability</subject><subject>Stability criteria</subject><subject>Stabilization</subject><subject>Steady-state</subject><subject>stochastic stability</subject><subject>Stochasticity</subject><subject>Studies</subject><issn>0018-9286</issn><issn>1558-2523</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpdkU1LJDEQhoOs4Kx6F7wE9uLBHvPZSR-H8WMXFEHn3qTT1RjtSdokI6w3_7kZRpbFU_FSz1MUvAidUDKnlDQXq8Vyzghlc8aIoFLtoRmVUldMMv4DzQihumqYrg_Qz5SeS6yFoDP08WB8H9bVyq3hHD9mk6G6hAl8Dz6XHOyTSdlZfBndkPEQIr4z8SW84eWTcT7houPFNI3OmuyCxzn8b5WDnRvd-253_wYRX0WTNhG2vvcwpiO0P5gxwfHXPESr66vV8nd1e3_zZ7m4rSyv61z1ttZKSTkQMljSdFyQpu8HbXRnQXHe867TWklhtTaGWSasslp2XceL0PBDdLY7O8XwuoGU27VLFsbReAib1FKmeS0UE6qgv76hz2ETfXmuUEJIqZQihSI7ysaQUoShnaJbm_i3paTdVtKWStptJe1XJUU53SkOAP7hNaOSMM4_AXNLiJE</recordid><startdate>201301</startdate><enddate>201301</enddate><creator>Yuksel, S.</creator><creator>Meyn, S. P.</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>F28</scope></search><sort><creationdate>201301</creationdate><title>Random-Time, State-Dependent Stochastic Drift for Markov Chains and Application to Stochastic Stabilization Over Erasure Channels</title><author>Yuksel, S. ; Meyn, S. P.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c366t-dc687755f00fc09b3409ddf8a8bce733d3bb88754c88aa2c24c7c85bbb30fc93</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Algorithms</topic><topic>Asymptotic stability</topic><topic>Channels</topic><topic>Computational fluid dynamics</topic><topic>Eigenvalues</topic><topic>Information theory</topic><topic>Markov chain Monte-Carlo (MCMC)</topic><topic>Markov chains</topic><topic>Markov processes</topic><topic>Mathematical analysis</topic><topic>networked control systems</topic><topic>Noise</topic><topic>Stability</topic><topic>Stability criteria</topic><topic>Stabilization</topic><topic>Steady-state</topic><topic>stochastic stability</topic><topic>Stochasticity</topic><topic>Studies</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Yuksel, S.</creatorcontrib><creatorcontrib>Meyn, S. P.</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><collection>Computer and Information Systems Abstracts</collection><collection>Electronics &amp; Communications Abstracts</collection><collection>Mechanical &amp; Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>ANTE: Abstracts in New Technology &amp; Engineering</collection><jtitle>IEEE transactions on automatic control</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Yuksel, S.</au><au>Meyn, S. P.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Random-Time, State-Dependent Stochastic Drift for Markov Chains and Application to Stochastic Stabilization Over Erasure Channels</atitle><jtitle>IEEE transactions on automatic control</jtitle><stitle>TAC</stitle><date>2013-01</date><risdate>2013</risdate><volume>58</volume><issue>1</issue><spage>47</spage><epage>59</epage><pages>47-59</pages><issn>0018-9286</issn><eissn>1558-2523</eissn><coden>IETAA9</coden><abstract>It is known that state-dependent, multi-step Lyapunov bounds lead to greatly simplified verification theorems for stability for large classes of Markov chain models. This is one component of the "fluid model" approach to stability of stochastic networks. In this paper we extend the general theory to randomized multi-step Lyapunov theory to obtain criteria for stability and steady-state performance bounds, such as finite moments. These results are applied to a remote stabilization problem, in which a controller receives measurements from an erasure channel with limited capacity. Based on the general results in the paper it is shown that stability of the closed loop system is assured provided that the channel capacity is greater than the logarithm of the unstable eigenvalue, plus an additional correction term. The existence of a finite second moment in steady-state is established under additional conditions.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TAC.2012.2204157</doi><tpages>13</tpages><oa>free_for_read</oa></addata></record>
fulltext fulltext_linktorsrc
identifier ISSN: 0018-9286
ispartof IEEE transactions on automatic control, 2013-01, Vol.58 (1), p.47-59
issn 0018-9286
1558-2523
language eng
recordid cdi_crossref_primary_10_1109_TAC_2012_2204157
source IEEE Electronic Library (IEL)
subjects Algorithms
Asymptotic stability
Channels
Computational fluid dynamics
Eigenvalues
Information theory
Markov chain Monte-Carlo (MCMC)
Markov chains
Markov processes
Mathematical analysis
networked control systems
Noise
Stability
Stability criteria
Stabilization
Steady-state
stochastic stability
Stochasticity
Studies
title Random-Time, State-Dependent Stochastic Drift for Markov Chains and Application to Stochastic Stabilization Over Erasure Channels
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-24T17%3A59%3A03IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_RIE&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Random-Time,%20State-Dependent%20Stochastic%20Drift%20for%20Markov%20Chains%20and%20Application%20to%20Stochastic%20Stabilization%20Over%20Erasure%20Channels&rft.jtitle=IEEE%20transactions%20on%20automatic%20control&rft.au=Yuksel,%20S.&rft.date=2013-01&rft.volume=58&rft.issue=1&rft.spage=47&rft.epage=59&rft.pages=47-59&rft.issn=0018-9286&rft.eissn=1558-2523&rft.coden=IETAA9&rft_id=info:doi/10.1109/TAC.2012.2204157&rft_dat=%3Cproquest_RIE%3E1283647247%3C/proquest_RIE%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1244557770&rft_id=info:pmid/&rft_ieee_id=6215023&rfr_iscdi=true