Discrete-Time Optimal Control via Local Policy Iteration Adaptive Dynamic Programming

In this paper, a discrete-time optimal control scheme is developed via a novel local policy iteration adaptive dynamic programming algorithm. In the discrete-time local policy iteration algorithm, the iterative value function and iterative control law can be updated in a subset of the state space, w...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	IEEE transactions on cybernetics Ročník 47; číslo 10; s. 3367 - 3379
Hlavní autoři:	Wei, Qinglai, Liu, Derong, Lin, Qiao, Song, Ruizhuo
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	United States IEEE 01.10.2017 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Adaptive algorithms Adaptive control Adaptive critic designs adaptive dynamic programming (ADP) Algorithms approximate dynamic programming Computer simulation Convergence Discrete-event systems Dynamic programming Heuristic algorithms Iterative algorithms Iterative methods local policy iteration Markov analysis neuro-dynamic programming Nonlinear systems OptimAL control Optimization Servers Time optimal control
ISSN:	2168-2267, 2168-2275
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Abstract	In this paper, a discrete-time optimal control scheme is developed via a novel local policy iteration adaptive dynamic programming algorithm. In the discrete-time local policy iteration algorithm, the iterative value function and iterative control law can be updated in a subset of the state space, where the computational burden is relaxed compared with the traditional policy iteration algorithm. Convergence properties of the local policy iteration algorithm are presented to show that the iterative value function is monotonically nonincreasing and converges to the optimum under some mild conditions. The admissibility of the iterative control law is proven, which shows that the control system can be stabilized under any of the iterative control laws, even if the iterative control law is updated in a subset of the state space. Finally, two simulation examples are given to illustrate the performance of the developed method.
AbstractList	In this paper, a discrete-time optimal control scheme is developed via a novel local policy iteration adaptive dynamic programming algorithm. In the discrete-time local policy iteration algorithm, the iterative value function and iterative control law can be updated in a subset of the state space, where the computational burden is relaxed compared with the traditional policy iteration algorithm. Convergence properties of the local policy iteration algorithm are presented to show that the iterative value function is monotonically nonincreasing and converges to the optimum under some mild conditions. The admissibility of the iterative control law is proven, which shows that the control system can be stabilized under any of the iterative control laws, even if the iterative control law is updated in a subset of the state space. Finally, two simulation examples are given to illustrate the performance of the developed method.
Author	Qiao Lin Derong Liu Qinglai Wei Ruizhuo Song
Author_xml	– sequence: 1 givenname: Qinglai surname: Wei fullname: Wei, Qinglai – sequence: 2 givenname: Derong surname: Liu fullname: Liu, Derong – sequence: 3 givenname: Qiao surname: Lin fullname: Lin, Qiao – sequence: 4 givenname: Ruizhuo surname: Song fullname: Song, Ruizhuo
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/27448382$$D View this record in MEDLINE/PubMed
BookMark	eNp9kTtv2zAUhYkiRfNofkAQoBDQpYtcXlJ8aEycJg1gIBmcIRNBUVcBA0l0KTqA_33p2vGQoVxIXnznkvecU3I0hhEJuQA6A6D1z-X8-XrGKMgZE1pSzT6REwZSl4wpcXQ4S3VMzqfplealc6nWX8gxU1WluWYn5OnGTy5iwnLpByweVskPti_mYUwx9MWbt8UiuFx5DL13m-I-YbTJh7G4am2G37C42Yx28K54jOEl2mHw48tX8rmz_YTn-_2MLG9_Lee_y8XD3f38alE6XtWp5K3klna0s1rUwBtgTrcSeVspKVSlGkoVQFMDCuBV27XOyabJd9la1jX8jPzYtV3F8GeNUzJDngb73o4Y1pMBncfnTAiV0e8f0NewjmP-nIGaSyagrkWmvu2pdTNga1YxuxE35t2vDMAOcDFMU8TugAA121jMNhazjcXsY8ka9UHjfPrnYYrW9_9VXu6UHhEPLykBAirG_wJAc5h9
CODEN	ITCEB8
CitedBy_id	crossref_primary_10_1109_TSMC_2024_3495821 crossref_primary_10_1016_j_nahs_2023_101338 crossref_primary_10_1109_TSMC_2019_2911900 crossref_primary_10_1109_TSMC_2016_2623766 crossref_primary_10_1016_j_conengprac_2023_105675 crossref_primary_10_1109_TNNLS_2020_3017762 crossref_primary_10_1016_j_neucom_2018_06_020 crossref_primary_10_1080_00207179_2022_2113438 crossref_primary_10_1109_TII_2021_3137816 crossref_primary_10_1109_TCYB_2019_2926631 crossref_primary_10_1109_TSMC_2019_2898370 crossref_primary_10_1155_2021_5549678 crossref_primary_10_1109_TCYB_2021_3085883 crossref_primary_10_1016_j_neucom_2018_10_091 crossref_primary_10_1109_TSMC_2018_2853089 crossref_primary_10_1002_rob_22053 crossref_primary_10_1002_oca_2391 crossref_primary_10_1002_rnc_4757 crossref_primary_10_1080_23307706_2021_2011792 crossref_primary_10_1109_TCYB_2021_3051035 crossref_primary_10_1016_j_ejor_2025_01_037 crossref_primary_10_1109_TAC_2018_2874707 crossref_primary_10_1109_TCYB_2022_3158898 crossref_primary_10_1109_TCYB_2019_2946122 crossref_primary_10_1109_TSMC_2017_2758849 crossref_primary_10_1109_TCYB_2020_3029825 crossref_primary_10_1016_j_ins_2019_05_071 crossref_primary_10_1109_TSMC_2018_2836194 crossref_primary_10_1002_oca_2907 crossref_primary_10_1016_j_compeleceng_2022_108015 crossref_primary_10_1109_TSMC_2018_2836952 crossref_primary_10_1016_j_ast_2020_106442 crossref_primary_10_1109_TCYB_2019_2906694 crossref_primary_10_1109_TII_2020_2972383 crossref_primary_10_1049_cth2_12520 crossref_primary_10_1016_j_oceaneng_2022_111802 crossref_primary_10_1109_TCSI_2024_3377641 crossref_primary_10_1109_TSMC_2019_2898389 crossref_primary_10_1177_1687814017751781 crossref_primary_10_1109_JAS_2024_124773 crossref_primary_10_3233_AIC_180766 crossref_primary_10_1002_rnc_70049 crossref_primary_10_1016_j_neucom_2020_05_012 crossref_primary_10_1109_TNNLS_2021_3053269 crossref_primary_10_1002_oca_2421 crossref_primary_10_1109_TNNLS_2017_2661865 crossref_primary_10_1109_TNNLS_2021_3071727 crossref_primary_10_1016_j_neucom_2019_03_029 crossref_primary_10_1109_TIE_2017_2650872 crossref_primary_10_1109_TSMC_2023_3318650 crossref_primary_10_1016_j_ins_2018_12_091 crossref_primary_10_1109_TNNLS_2016_2638863 crossref_primary_10_1109_TSMC_2018_2837899 crossref_primary_10_1007_s40998_019_00203_9 crossref_primary_10_1109_TCSII_2023_3291399 crossref_primary_10_1109_TSMC_2023_3327492 crossref_primary_10_1109_TCYB_2018_2823199 crossref_primary_10_1109_TSMC_2020_3042876 crossref_primary_10_1109_TCYB_2023_3332079 crossref_primary_10_1016_j_sysconle_2024_105819 crossref_primary_10_1016_j_neucom_2018_10_072 crossref_primary_10_1109_TCYB_2018_2818747 crossref_primary_10_1109_TSMC_2017_2748964 crossref_primary_10_1109_TSMC_2019_2962629 crossref_primary_10_1109_TCSI_2024_3492255 crossref_primary_10_1109_TSMC_2019_2962103 crossref_primary_10_1002_oca_2771 crossref_primary_10_1109_TNNLS_2023_3245980 crossref_primary_10_1016_j_neucom_2020_04_140 crossref_primary_10_1016_j_automatica_2020_109117 crossref_primary_10_1016_j_neucom_2018_12_033 crossref_primary_10_1109_TNNLS_2024_3392237 crossref_primary_10_1016_j_neucom_2020_11_014 crossref_primary_10_1002_rnc_4342 crossref_primary_10_1109_TCYB_2019_2901268 crossref_primary_10_1109_JSYST_2024_3432796
Cites_doi	10.1006/jsco.1997.0119 10.1109/72.914523 10.1109/TASE.2014.2303139 10.1109/TAC.2014.2317301 10.1109/TNNLS.2015.2461452 10.1109/TCYB.2016.2523878 10.1109/TASE.2013.2284545 10.1007/s10479-012-1128-z 10.1109/TSMCB.2008.926614 10.1109/TNNLS.2015.2401334 10.1109/TPWRD.2009.2016258 10.1109/TCYB.2015.2417170 10.1016/j.automatica.2004.11.034 10.1109/TCYB.2014.2313915 10.1109/TSG.2012.2233224 10.1109/TFUZZ.2014.2310238 10.1109/TSMCB.2012.2203336 10.1109/TASE.2013.2280974 10.1109/MCS.2012.2214134 10.1109/TIE.2013.2273477 10.1016/j.neucom.2012.11.021 10.1109/TIE.2014.2345343 10.1016/j.ins.2015.04.044 10.1109/JAS.2014.7004681 10.1109/TCYB.2014.2384016 10.1109/TSG.2014.2346740 10.1109/TCYB.2014.2354377 10.1049/iet-cta.2012.0486 10.1109/JAS.2014.7004665 10.1109/TNNLS.2015.2441712 10.1109/TIE.2016.2530789 10.1016/j.automatica.2014.10.047 10.1007/s11432-013-4954-y 10.1109/TNNLS.2015.2424971 10.1109/TCYB.2016.2542923 10.1016/j.automatica.2014.05.011 10.1109/TSMCB.2012.2216523 10.1109/TIE.2014.2388198 10.7551/mitpress/4939.003.0007 10.1007/s11432-015-5462-z 10.1109/TIE.2014.2301770 10.1109/TNNLS.2014.2358227 10.1287/moor.1110.0532 10.1109/TCYB.2014.2314612 10.1109/TNNLS.2013.2281663 10.1109/TAC.2015.2414811 10.1109/TCYB.2015.2492242 10.1109/TIE.2014.2361485 10.1016/j.automatica.2014.02.015 10.1109/TCYB.2016.2519445 10.1109/TAC.2006.878720 10.1109/TNNLS.2012.2236354 10.1109/TSMCC.2002.801727 10.1109/TNNLS.2012.2234133 10.1109/TNNLS.2015.2399020 10.1109/TNNLS.2015.2464080 10.1109/TCYB.2015.2421338 10.1016/j.automatica.2010.10.033 10.1109/TCYB.2015.2509646 10.1109/72.623201 10.1109/TNNLS.2014.2329942 10.1109/JAS.2016.7510262 10.1016/j.automatica.2015.06.001 10.1109/TNNLS.2014.2306201
ContentType	Journal Article
Copyright	Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2017
Copyright_xml	– notice: Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2017
DBID	97E RIA RIE AAYXX CITATION NPM 7SC 7SP 7TB 8FD F28 FR3 H8D JQ2 L7M L~C L~D 7X8
DOI	10.1109/TCYB.2016.2586082
DatabaseName	IEEE All-Society Periodicals Package (ASPP) 2005–Present IEEE All-Society Periodicals Package (ASPP) 1998–Present IEEE Xplore CrossRef PubMed Computer and Information Systems Abstracts Electronics & Communications Abstracts Mechanical & Transportation Engineering Abstracts Technology Research Database ANTE: Abstracts in New Technology & Engineering Engineering Research Database Aerospace Database ProQuest Computer Science Collection Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Academic Computer and Information Systems Abstracts Professional MEDLINE - Academic
DatabaseTitle	CrossRef PubMed Aerospace Database Technology Research Database Computer and Information Systems Abstracts – Academic Mechanical & Transportation Engineering Abstracts Electronics & Communications Abstracts ProQuest Computer Science Collection Computer and Information Systems Abstracts Engineering Research Database Advanced Technologies Database with Aerospace ANTE: Abstracts in New Technology & Engineering Computer and Information Systems Abstracts Professional MEDLINE - Academic
DatabaseTitleList	MEDLINE - Academic PubMed Aerospace Database
Database_xml	– sequence: 1 dbid: NPM name: PubMed url: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 2 dbid: RIE name: IEEE Electronic Library (IEL) url: https://ieeexplore.ieee.org/ sourceTypes: Publisher – sequence: 3 dbid: 7X8 name: MEDLINE - Academic url: https://search.proquest.com/medline sourceTypes: Aggregation Database
DeliveryMethod	fulltext_linktorsrc
Discipline	Sciences (General)
EISSN	2168-2275
EndPage	3379
ExternalDocumentID	27448382 10_1109_TCYB_2016_2586082 7515142
Genre	orig-research Journal Article
GrantInformation_xml	– fundername: National Natural Science Foundation of China grantid: 61233001; 61273140; 61374105; 61503379; 61533017; 61304079; U1501251 funderid: 10.13039/501100001809
GroupedDBID	0R~ 4.4 6IK 97E AAJGR AARMG AASAJ AAWTH ABAZT ABQJQ ABVLG ACIWK AENEX AGQYO AGSQL AHBIQ AKJIK AKQYR ALMA_UNASSIGNED_HOLDINGS ATWAV BEFXN BFFAM BGNUA BKEBE BPEOZ EBS EJD HZ~ IFIPE IPLJI JAVBF M43 O9- OCL PQQKQ RIA RIE RNS AAYXX CITATION NPM RIG 7SC 7SP 7TB 8FD F28 FR3 H8D JQ2 L7M L~C L~D 7X8
ID	FETCH-LOGICAL-c349t-3d63a0f0fa85913b12c8d6e3d4765747b00711b91e5134dfdcc6bbb916da2fb3
IEDL.DBID	RIE
ISICitedReferencesCount	102
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000409311800034&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	2168-2267
IngestDate	Sat Sep 27 19:36:37 EDT 2025 Sun Nov 09 07:41:17 EST 2025 Thu Jan 02 23:09:06 EST 2025 Sat Nov 29 06:48:33 EST 2025 Tue Nov 18 21:32:53 EST 2025 Tue Aug 26 16:38:57 EDT 2025
IsPeerReviewed	true
IsScholarly	true
Issue	10
Language	English
License	https://ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html
LinkModel	DirectLink
MergedId	FETCHMERGED-LOGICAL-c349t-3d63a0f0fa85913b12c8d6e3d4765747b00711b91e5134dfdcc6bbb916da2fb3
Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23
PMID	27448382
PQID	1936251995
PQPubID	85422
PageCount	13
ParticipantIDs	crossref_primary_10_1109_TCYB_2016_2586082 pubmed_primary_27448382 ieee_primary_7515142 crossref_citationtrail_10_1109_TCYB_2016_2586082 proquest_journals_1936251995 proquest_miscellaneous_1826732557
PublicationCentury	2000
PublicationDate	2017-10-01
PublicationDateYYYYMMDD	2017-10-01
PublicationDate_xml	– month: 10 year: 2017 text: 2017-10-01 day: 01
PublicationDecade	2010
PublicationPlace	United States
PublicationPlace_xml	– name: United States – name: Piscataway
PublicationTitle	IEEE transactions on cybernetics
PublicationTitleAbbrev	TCYB
PublicationTitleAlternate	IEEE Trans Cybern
PublicationYear	2017
Publisher	IEEE The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher_xml	– name: IEEE – name: The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
References	ref57 ref13 ref56 ref12 ref59 ref15 ref58 ref14 ref52 ref55 ref11 ref54 ref10 ref16 ref19 ref18 liu (ref34) 2013; 43 ref51 ref50 ref46 ref45 ref48 ref47 ref42 ref41 ref44 ref43 ref49 ref8 ref7 ref9 ref4 ref3 ref6 ref5 bertsekas (ref33) 2007 watkins (ref17) 1989 ref35 ref37 ref36 werbos (ref1) 1977; 22 ref30 ref32 busoniu (ref39) 2010 ref38 bertsekas (ref31) 1996 ref71 ref70 ref68 ref24 ref67 ref23 ref26 ref69 ref25 ref64 ref20 ref63 ref66 ref22 ref65 ref21 ref28 sutton (ref40) 1998 ref27 ref29 werbos (ref2) 1991 ref60 liu (ref53) 2014; 25 ref62 ref61
References_xml	– ident: ref63 doi: 10.1006/jsco.1997.0119 – ident: ref62 doi: 10.1109/72.914523 – ident: ref20 doi: 10.1109/TASE.2014.2303139 – ident: ref25 doi: 10.1109/TAC.2014.2317301 – ident: ref10 doi: 10.1109/TNNLS.2015.2461452 – ident: ref60 doi: 10.1109/TCYB.2016.2523878 – ident: ref8 doi: 10.1109/TASE.2013.2284545 – ident: ref19 doi: 10.1007/s10479-012-1128-z – ident: ref32 doi: 10.1109/TSMCB.2008.926614 – ident: ref54 doi: 10.1109/TNNLS.2015.2401334 – ident: ref66 doi: 10.1109/TPWRD.2009.2016258 – ident: ref52 doi: 10.1109/TCYB.2015.2417170 – ident: ref42 doi: 10.1016/j.automatica.2004.11.034 – ident: ref55 doi: 10.1109/TCYB.2014.2313915 – ident: ref4 doi: 10.1109/TSG.2012.2233224 – ident: ref46 doi: 10.1109/TFUZZ.2014.2310238 – ident: ref57 doi: 10.1109/TSMCB.2012.2203336 – ident: ref38 doi: 10.1109/TASE.2013.2280974 – ident: ref30 doi: 10.1109/MCS.2012.2214134 – ident: ref64 doi: 10.1109/TIE.2013.2273477 – ident: ref29 doi: 10.1016/j.neucom.2012.11.021 – ident: ref14 doi: 10.1109/TIE.2014.2345343 – ident: ref61 doi: 10.1016/j.ins.2015.04.044 – ident: ref67 doi: 10.1109/JAS.2014.7004681 – ident: ref58 doi: 10.1109/TCYB.2014.2384016 – ident: ref9 doi: 10.1109/TSG.2014.2346740 – ident: ref37 doi: 10.1109/TCYB.2014.2354377 – year: 2007 ident: ref33 publication-title: Dynamic Programming and Optimal Control – ident: ref28 doi: 10.1049/iet-cta.2012.0486 – ident: ref68 doi: 10.1109/JAS.2014.7004665 – ident: ref12 doi: 10.1109/TNNLS.2015.2441712 – year: 1989 ident: ref17 article-title: Learning from delayed rewards – ident: ref65 doi: 10.1109/TIE.2016.2530789 – ident: ref11 doi: 10.1016/j.automatica.2014.10.047 – ident: ref71 doi: 10.1007/s11432-013-4954-y – ident: ref22 doi: 10.1109/TNNLS.2015.2424971 – ident: ref21 doi: 10.1109/TCYB.2016.2542923 – ident: ref49 doi: 10.1016/j.automatica.2014.05.011 – year: 1996 ident: ref31 publication-title: Neuro-Dynamic Programming – volume: 43 start-page: 779 year: 2013 ident: ref34 article-title: Finite-approximation-error-based optimal control approach for discrete-time nonlinear systems publication-title: IEEE Trans Cybern doi: 10.1109/TSMCB.2012.2216523 – ident: ref24 doi: 10.1109/TIE.2014.2388198 – start-page: 67 year: 1991 ident: ref2 article-title: A menu of designs for reinforcement learning over time publication-title: Neural Networks for Control doi: 10.7551/mitpress/4939.003.0007 – ident: ref70 doi: 10.1007/s11432-015-5462-z – ident: ref26 doi: 10.1109/TIE.2014.2301770 – volume: 22 start-page: 25 year: 1977 ident: ref1 article-title: Advanced forecasting methods for global crisis warning and models of intelligence publication-title: Gen Syst Yearbook – year: 2010 ident: ref39 publication-title: Reinforcement Learning and Dynamic Programming Using Function Approximators – ident: ref51 doi: 10.1109/TNNLS.2014.2358227 – ident: ref18 doi: 10.1287/moor.1110.0532 – year: 1998 ident: ref40 publication-title: Reinforcement Learning An Introduction – ident: ref27 doi: 10.1109/TCYB.2014.2314612 – volume: 25 start-page: 621 year: 2014 ident: ref53 article-title: Policy iteration adaptive dynamic programming algorithm for discrete-time nonlinear systems publication-title: IEEE Trans Neural Netw Learn Syst doi: 10.1109/TNNLS.2013.2281663 – ident: ref15 doi: 10.1109/TAC.2015.2414811 – ident: ref36 doi: 10.1109/TCYB.2015.2492242 – ident: ref6 doi: 10.1109/TIE.2014.2361485 – ident: ref50 doi: 10.1016/j.automatica.2014.02.015 – ident: ref13 doi: 10.1109/TCYB.2016.2519445 – ident: ref35 doi: 10.1109/TAC.2006.878720 – ident: ref48 doi: 10.1016/j.automatica.2014.10.047 – ident: ref56 doi: 10.1109/TNNLS.2012.2236354 – ident: ref41 doi: 10.1109/TSMCC.2002.801727 – ident: ref5 doi: 10.1109/TNNLS.2012.2234133 – ident: ref44 doi: 10.1109/TNNLS.2015.2399020 – ident: ref3 doi: 10.1109/TNNLS.2015.2464080 – ident: ref45 doi: 10.1109/TCYB.2015.2421338 – ident: ref47 doi: 10.1016/j.automatica.2010.10.033 – ident: ref59 doi: 10.1109/TCYB.2015.2509646 – ident: ref16 doi: 10.1109/72.623201 – ident: ref23 doi: 10.1109/TNNLS.2014.2329942 – ident: ref69 doi: 10.1109/JAS.2016.7510262 – ident: ref7 doi: 10.1016/j.automatica.2015.06.001 – ident: ref43 doi: 10.1109/TNNLS.2014.2306201
SSID	ssj0000816898
Score	2.464164
Snippet	In this paper, a discrete-time optimal control scheme is developed via a novel local policy iteration adaptive dynamic programming algorithm. In the...
SourceID	proquest pubmed crossref ieee
SourceType	Aggregation Database Index Database Enrichment Source Publisher
StartPage	3367
SubjectTerms	Adaptive algorithms Adaptive control Adaptive critic designs adaptive dynamic programming (ADP) Algorithms approximate dynamic programming Computer simulation Convergence Discrete-event systems Dynamic programming Heuristic algorithms Iterative algorithms Iterative methods local policy iteration Markov analysis neuro-dynamic programming Nonlinear systems OptimAL control Optimization Servers Time optimal control
Title	Discrete-Time Optimal Control via Local Policy Iteration Adaptive Dynamic Programming
URI	https://ieeexplore.ieee.org/document/7515142 https://www.ncbi.nlm.nih.gov/pubmed/27448382 https://www.proquest.com/docview/1936251995 https://www.proquest.com/docview/1826732557
Volume	47
WOSCitedRecordID	wos000409311800034&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText	1
inHoldings	1
isFullTextHit
isPrint
journalDatabaseRights	– providerCode: PRVIEE databaseName: IEEE Electronic Library (IEL) customDbUrl: eissn: 2168-2275 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0000816898 issn: 2168-2267 databaseCode: RIE dateStart: 20130101 isFulltext: true titleUrlDefault: https://ieeexplore.ieee.org/ providerName: IEEE
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1LT9wwEB5RxIFLWx5tUyhypR6gqiGOHTs-0qWolRBwWKTtKfIr0kplF7G7_H7Gjjfqoa3UW6LYSeQZe76xZ74B-FRLw0tTeSq4UFQEwajtmKSVqHXpg7eqSYnCV-r6uplM9O0GfBlyYUIIKfgsnMbLdJbv524Vt8rOFBpfJnDBfaGU6nO1hv2UVEAilb6t8IIiqlD5EJOV-mw8-vk1xnHJ06puJJq9SAKs0DVJDHy_WaRUYuXvaDNZnctX__e_r-FlRpfkvFeHHdgIs13YyfN3QY4zyfTJHtxdTHHBQMRMYxIIucGV4x57jvrIdfI0NeQqmjnSEweTH4l9GYVIzr15iGskueiL2ZPbPsTrHo3gPowvv41H32kusUAdF3pJuZfclF3Zmchjxy2rXONl4F4oWaOnYSMEYVazUDMufOedk9bivfSm6ix_A5uz-Sy8A8KCqrjhjbTaC2sQ5gSH6KerndTelaaAcj3Krcv047EKxq82uSGlbqOM2iijNsuogM9Dl4eee-NfjfeiAIaGeewLOFyLss2zc9EiaJUxY1fXBXwcHuO8ioclZhbmK2yDfpfi6HCpAt72KjC8e6057__8zQPYrqLxTyF_h7C5fFyFD7DlnpbTxeMRKu-kOUrK-wxS3ecp
linkProvider	IEEE
linkToHtml	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1Lb9QwEB5VLRJcKKVQAgWMxAEQbuNH7ORYtlStWJYeFqmcIr8irUR3q-5ufz9jxxtxACRuiWInkWfs-cae-QbgbaWMKA33VAqpqQySUdsxRbmsmtIHb3WdEoXHejKpr66ayy34OOTChBBS8Fk4ipfpLN8v3DpulR1rNL5M4oK7U0nJWZ-tNeyopBISqfgtxwuKuELnY0xWNsfT0Y9PMZJLHfGqVmj4Ig2wRuckcfD9ZpNSkZW_481kd852_--PH8HDjC_JSa8Qe7AV5o9hL8_gJXmXaabf78P30xkuGYiZaUwDId9w7bjGnqM-dp3czQwZR0NHeupgcpH4l1GM5MSbm7hKktO-nD257IO8rtEMPoHp2efp6JzmIgvUCdmsqPBKmLIrOxOZ7IRl3NVeBeGlVhX6GjaCEGYbFiompO-8c8pavFfe8M6Kp7A9X8zDMyAsaC6MqJVtvLQGgU5wiH-6yqnGu9IUUG5GuXWZgDzWwfjZJkekbNooozbKqM0yKuDD0OWmZ9_4V-P9KIChYR77Ag43omzz_Fy2CFtVzNltqgLeDI9xZsXjEjMPizW2Qc9LC3S5dAEHvQoM795ozvM_f_M13D-ffh2344vJlxfwgEcokAIAD2F7dbsOL-Geu1vNlrevkgr_Ag1k6Yg
openUrl	ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Discrete-Time+Optimal+Control+via+Local+Policy+Iteration+Adaptive+Dynamic+Programming&rft.jtitle=IEEE+transactions+on+cybernetics&rft.au=Wei%2C+Qinglai&rft.au=Liu%2C+Derong&rft.au=Lin%2C+Qiao&rft.au=Song%2C+Ruizhuo&rft.date=2017-10-01&rft.issn=2168-2267&rft.eissn=2168-2275&rft.volume=47&rft.issue=10&rft.spage=3367&rft.epage=3379&rft_id=info:doi/10.1109%2FTCYB.2016.2586082&rft.externalDBID=n%2Fa&rft.externalDocID=10_1109_TCYB_2016_2586082
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2168-2267&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2168-2267&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2168-2267&client=summon