Security-Based Distributionally Robust Optimization Self-Triggered SMPC for Constrained Cyber-Physical Systems Subject to Unknown Disturbances and Denial-of-Service Attacks

In this article, we propose a distributionally robust optimization-based self-triggered stochastic model predictive control (DRSMPC) algorithm for linear discrete systems that are subject to unbounded stochastic disturbances and Denial-of-Service (DoS) attacks. Assuming that only the first and secon...

Full description

Saved in:
Bibliographic Details
Published inIEEE internet of things journal Vol. 12; no. 12; pp. 21757 - 21769
Main Authors Chen, Yadong, Cheng, Peng
Format Journal Article
LanguageEnglish
Published Piscataway IEEE 15.06.2025
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Algorithms
Chance constraint
Constraints
Control systems
Cyber-physical systems
Cybersecurity
Denial of service attacks
Discrete systems
distributionally robust optimization
Disturbances
Event detection
Internet of Things
Optimization
Prediction algorithms
Predictive control
Predictive models
Quadratic forms
Robustness (mathematics)
Sampling
self-triggered stochastic model predictive control (MPC)
Sensors
Stochastic models
Stochastic processes
Vectors
Online AccessGet full text

Cover

Abstract In this article, we propose a distributionally robust optimization-based self-triggered stochastic model predictive control (DRSMPC) algorithm for linear discrete systems that are subject to unbounded stochastic disturbances and Denial-of-Service (DoS) attacks. Assuming that only the first and second moments of the disturbances are available, we transform the objective function into a compact quadratic form and reformulate the state chance constraint into second-order cone constraint, which enhance tractability during the solution process. To reduce communication and sampling times within the system, we introduce a self-triggering update framework, which computes the sampling instants and the control input sequences between consecutive sampling instants based on the sampled state. The main contribution of DRSMPC is to deal with unknown disturbances, reduce the unnecessary sampling also be able to defend against DoS attacks. Furthermore, we demonstrate that DRSMPC is recursively feasible and cyber-physical systems (CPSs) remaining quadratic stability. Numerical simulations validate the effectiveness of the proposed algorithm.
AbstractList In this article, we propose a distributionally robust optimization-based self-triggered stochastic model predictive control (DRSMPC) algorithm for linear discrete systems that are subject to unbounded stochastic disturbances and Denial-of-Service (DoS) attacks. Assuming that only the first and second moments of the disturbances are available, we transform the objective function into a compact quadratic form and reformulate the state chance constraint into second-order cone constraint, which enhance tractability during the solution process. To reduce communication and sampling times within the system, we introduce a self-triggering update framework, which computes the sampling instants and the control input sequences between consecutive sampling instants based on the sampled state. The main contribution of DRSMPC is to deal with unknown disturbances, reduce the unnecessary sampling also be able to defend against DoS attacks. Furthermore, we demonstrate that DRSMPC is recursively feasible and cyber-physical systems (CPSs) remaining quadratic stability. Numerical simulations validate the effectiveness of the proposed algorithm.
Author Chen, Yadong
Cheng, Peng
Author_xml – sequence: 1
  givenname: Yadong
  surname: Chen
  fullname: Chen, Yadong
  email: 2021326210015@stu.scu.edu.cn
  organization: School of Aeronautics and Astronautics, Sichuan University, Chengdu, China
– sequence: 2
  givenname: Peng
  orcidid: 0009-0003-0933-0305
  surname: Cheng
  fullname: Cheng, Peng
  email: CP17208263046@163.com
  organization: School of Aeronautics and Astronautics, Sichuan University, Chengdu, China
BookMark eNpNkd1u1DAQhS1UJErbB0DiwhLXXvyXOL4s4a-o1VZkex05zqR4m7UX22kVnomHJMv2olczOjrfzGjOW3TigweE3jG6Yozqjz-u1psVp7xYiUJWkhav0CkXXBFZlvzkRf8GXaS0pZQuWMF0eYr-NmCn6PJMPpkEPf7sUo6um7IL3ozjjH-GbkoZr_fZ7dwfc9BxA-NANtHd30NcmObmtsZDiLgOfqGN84tYzx1EcvtrTs6aETdzyrBLuJm6LdiMc8B3_sGHJ_9_5RQ74y0kbPxyA3hnRhIG0kB8dBbwZc7GPqRz9HowY4KL53qG7r5-2dTfyfX621V9eU0sl2UmpuqtKjo7DBUoKYoKmJV9z5XmJRSU68oazkteUilUQVnHQXdScyPNQHvdizP04Th3H8PvCVJut2GKyz9SKzhTSgktxeJiR5eNIaUIQ7uPbmfi3DLaHnJpD7m0h1za51wW5v2RcQDwwq8Zl4qLf-vTjl8
CODEN IITJAU
Cites_doi 10.1109/TASE.2022.3222182
10.1016/j.automatica.2021.109870
10.1109/TSMC.2023.3331231
10.1016/j.automatica.2020.109352
10.1016/j.automatica.2022.110424
10.1109/TCYB.2024.3349528
10.1016/j.ins.2020.07.004
10.1137/21M1465548
10.1109/tcns.2024.3425646
10.1109/TII.2019.2963294
10.1109/TAC.2023.3243863
10.1016/j.compchemeng.2019.106638
10.1016/j.automatica.2021.109519
10.1109/TCYB.2019.2936413
10.1109/TIA.2015.2501761
10.1016/j.automatica.2019.03.009
10.1016/j.automatica.2023.111014
10.1109/TCSII.2024.3358016
10.1016/j.automatica.2022.110208
10.1016/j.automatica.2020.109129
10.1016/j.automatica.2020.109402
10.1002/rnc.1249
10.1109/TAC.2022.3157131
10.1016/j.jfranklin.2021.04.034
10.1007/s10957-006-9084-x
10.1016/j.automatica.2023.111050
10.1016/j.tre.2023.103025
10.1109/TVT.2022.3215966
10.1016/j.automatica.2020.108803
10.1109/TAC.2010.2086553
10.1109/TAC.2023.3244116
10.1016/j.automatica.2024.111833
10.1016/j.jprocont.2016.03.005
10.1016/j.oceaneng.2022.113262
10.1109/JIOT.2024.3392563
10.1016/j.automatica.2016.04.008
10.1109/TAC.2021.3124750
10.1109/LCSYS.2019.2918763
10.1016/j.automatica.2022.110533
10.1109/TAC.2020.2987649
10.1016/j.automatica.2024.111917
10.1109/TAC.2023.3338749
10.1016/j.automatica.2018.02.017
10.1016/j.epsr.2020.106642
10.1016/j.automatica.2021.110055
10.1109/TVT.2023.3266829
10.1016/j.automatica.2023.111493
ContentType Journal Article
Copyright Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2025
Copyright_xml – notice: Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2025
DBID 97E
RIA
RIE
AAYXX
CITATION
7SC
8FD
JQ2
L7M
L~C
L~D
DOI 10.1109/JIOT.2025.3548405
DatabaseName IEEE All-Society Periodicals Package (ASPP) 2005–Present
IEEE All-Society Periodicals Package (ASPP) 1998–Present
IEEE Xplore
CrossRef
Computer and Information Systems Abstracts
Technology Research Database
ProQuest Computer Science Collection
Advanced Technologies Database with Aerospace
Computer and Information Systems Abstracts – Academic
Computer and Information Systems Abstracts Professional
DatabaseTitle CrossRef
Computer and Information Systems Abstracts
Technology Research Database
Computer and Information Systems Abstracts – Academic
Advanced Technologies Database with Aerospace
ProQuest Computer Science Collection
Computer and Information Systems Abstracts Professional
DatabaseTitleList Computer and Information Systems Abstracts
Database_xml – sequence: 1
  dbid: RIE
  name: IEEE Electronic Library (IEL)
  url: https://proxy.k.utb.cz/login?url=https://ieeexplore.ieee.org/
  sourceTypes: Publisher
DeliveryMethod fulltext_linktorsrc
Discipline Computer Science
EISSN 2327-4662
EndPage 21769
ExternalDocumentID 10_1109_JIOT_2025_3548405
10912472
Genre orig-research
GroupedDBID 0R~
6IK
97E
AAJGR
AARMG
AASAJ
AAWTH
ABAZT
ABJNI
ABQJQ
ABVLG
AGQYO
AHBIQ
AKJIK
AKQYR
ALMA_UNASSIGNED_HOLDINGS
ATWAV
BEFXN
BFFAM
BGNUA
BKEBE
BPEOZ
EBS
IFIPE
IPLJI
JAVBF
M43
OCL
PQQKQ
RIA
RIE
AAYXX
CITATION
7SC
8FD
JQ2
L7M
L~C
L~D
ID FETCH-LOGICAL-c246t-a8dc75bcff8e74358e1c4dd27926e50298ca226260437501b2e9b492a4af0d9d3
IEDL.DBID RIE
ISSN 2327-4662
IngestDate Thu Aug 28 13:11:11 EDT 2025
Thu Jul 03 08:47:02 EDT 2025
Wed Jun 25 06:00:24 EDT 2025
IsPeerReviewed false
IsScholarly true
Issue 12
Language English
License https://ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html
https://doi.org/10.15223/policy-029
https://doi.org/10.15223/policy-037
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c246t-a8dc75bcff8e74358e1c4dd27926e50298ca226260437501b2e9b492a4af0d9d3
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ORCID 0009-0003-0933-0305
PQID 3217773943
PQPubID 2040421
PageCount 13
ParticipantIDs proquest_journals_3217773943
ieee_primary_10912472
crossref_primary_10_1109_JIOT_2025_3548405
PublicationCentury 2000
PublicationDate 2025-06-15
PublicationDateYYYYMMDD 2025-06-15
PublicationDate_xml – month: 06
  year: 2025
  text: 2025-06-15
  day: 15
PublicationDecade 2020
PublicationPlace Piscataway
PublicationPlace_xml – name: Piscataway
PublicationTitle IEEE internet of things journal
PublicationTitleAbbrev JIoT
PublicationYear 2025
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 ref13
ref35
ref12
ref34
ref15
ref37
ref14
ref36
ref31
ref30
ref11
ref33
ref10
ref32
ref2
ref1
ref17
ref39
ref16
ref38
ref19
ref18
ref24
ref46
ref23
ref45
ref26
ref48
ref25
ref20
ref42
ref41
ref22
ref44
ref21
ref43
Petersen (ref47) 2008; 7
ref28
ref27
ref29
ref8
ref7
ref9
ref4
ref3
ref6
ref5
ref40
References_xml – ident: ref2
  doi: 10.1109/TASE.2022.3222182
– ident: ref44
  doi: 10.1016/j.automatica.2021.109870
– ident: ref15
  doi: 10.1109/TSMC.2023.3331231
– ident: ref26
  doi: 10.1016/j.automatica.2020.109352
– ident: ref43
  doi: 10.1016/j.automatica.2022.110424
– ident: ref22
  doi: 10.1109/TCYB.2024.3349528
– ident: ref41
  doi: 10.1016/j.ins.2020.07.004
– ident: ref33
  doi: 10.1137/21M1465548
– ident: ref14
  doi: 10.1109/tcns.2024.3425646
– ident: ref39
  doi: 10.1109/TII.2019.2963294
– ident: ref16
  doi: 10.1109/TAC.2023.3243863
– ident: ref6
  doi: 10.1016/j.compchemeng.2019.106638
– ident: ref10
  doi: 10.1016/j.automatica.2021.109519
– ident: ref11
  doi: 10.1109/TCYB.2019.2936413
– ident: ref3
  doi: 10.1109/TIA.2015.2501761
– ident: ref13
  doi: 10.1016/j.automatica.2019.03.009
– ident: ref4
  doi: 10.1016/j.automatica.2023.111014
– ident: ref38
  doi: 10.1109/TCSII.2024.3358016
– ident: ref28
  doi: 10.1016/j.automatica.2022.110208
– ident: ref27
  doi: 10.1016/j.automatica.2020.109129
– ident: ref30
  doi: 10.1016/j.automatica.2020.109402
– ident: ref5
  doi: 10.1002/rnc.1249
– ident: ref29
  doi: 10.1109/TAC.2022.3157131
– ident: ref42
  doi: 10.1016/j.jfranklin.2021.04.034
– ident: ref35
  doi: 10.1007/s10957-006-9084-x
– ident: ref1
  doi: 10.1016/j.automatica.2023.111050
– ident: ref34
  doi: 10.1016/j.tre.2023.103025
– ident: ref40
  doi: 10.1109/TVT.2022.3215966
– ident: ref23
  doi: 10.1016/j.automatica.2020.108803
– ident: ref32
  doi: 10.1109/TAC.2010.2086553
– ident: ref24
  doi: 10.1109/TAC.2023.3244116
– ident: ref37
  doi: 10.1016/j.automatica.2024.111833
– ident: ref31
  doi: 10.1016/j.jprocont.2016.03.005
– ident: ref25
  doi: 10.1016/j.oceaneng.2022.113262
– ident: ref12
  doi: 10.1109/JIOT.2024.3392563
– ident: ref48
  doi: 10.1016/j.automatica.2016.04.008
– ident: ref36
  doi: 10.1109/TAC.2021.3124750
– ident: ref46
  doi: 10.1109/LCSYS.2019.2918763
– ident: ref9
  doi: 10.1016/j.automatica.2022.110533
– ident: ref17
  doi: 10.1109/TAC.2020.2987649
– ident: ref20
  doi: 10.1016/j.automatica.2024.111917
– ident: ref21
  doi: 10.1109/TAC.2023.3338749
– ident: ref45
  doi: 10.1016/j.automatica.2018.02.017
– ident: ref8
  doi: 10.1016/j.epsr.2020.106642
– ident: ref18
  doi: 10.1016/j.automatica.2021.110055
– volume: 7
  volume-title: The Matrix Cookbook
  year: 2008
  ident: ref47
– ident: ref7
  doi: 10.1109/TVT.2023.3266829
– ident: ref19
  doi: 10.1016/j.automatica.2023.111493
SSID ssj0001105196
Score 2.3430219
Snippet In this article, we propose a distributionally robust optimization-based self-triggered stochastic model predictive control (DRSMPC) algorithm for linear...
SourceID proquest
crossref
ieee
SourceType Aggregation Database
Index Database
Publisher
StartPage 21757
SubjectTerms Algorithms
Chance constraint
Constraints
Control systems
Cyber-physical systems
Cybersecurity
Denial of service attacks
Discrete systems
distributionally robust optimization
Disturbances
Event detection
Internet of Things
Optimization
Prediction algorithms
Predictive control
Predictive models
Quadratic forms
Robustness (mathematics)
Sampling
self-triggered stochastic model predictive control (MPC)
Sensors
Stochastic models
Stochastic processes
Vectors
Title Security-Based Distributionally Robust Optimization Self-Triggered SMPC for Constrained Cyber-Physical Systems Subject to Unknown Disturbances and Denial-of-Service Attacks
URI https://ieeexplore.ieee.org/document/10912472
https://www.proquest.com/docview/3217773943
Volume 12
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV1LT8MwDI6AExfeiPFSDpyQMtY2SdsjDBAg8RDbJG5V0iYcGC3a2sP4TfxI7DQTCITErarSNJId-3Ni-yPkKCgg6LI2ZiKQmsFODFkqrWLWRiZNjQq5cVm-d_JqxG-exJMvVne1MMYYl3xmuvjo7vKLKm_wqOwEm1iGPAaLuwiRW1us9XWgEiAakf7mEoae3FzfDyECDEU3AlzOkaHum-9xZCq_LLBzK5er5G6-oDab5KXb1Lqbv__o1fjvFa-RFQ8w6WmrEetkwZQbZHVO3kD9Xt4kHwPPXMfOwJEV9Bw76HryKzUez-hjpZtpTe_Bprz6Yk06MGPLhhDQPyPFJx3cPvQpoF6KtJ-ObAJe9mfaTNiDlz_1LdEpWCg88qF1RUclnuSV7pfNRKPeTakqYQ2Y-TdmlWXehNHTusYmAFtkdHkx7F8xT93A8pDLmqmkyGOhc2sTAxhFJCbIeVFgt0JpBLZ9zxUAPwimeASYJdChSTVPQ8WV7RVpEW2TpbIqzQ6hCagZTCN7AEW5FlIpIZMIXC8EroCebIccz4WavbUdOjIX2fTSDDUgQw3IvAZ0yBYK6dvAVj4dsj_Xg8xv4mkWQbgWx1HKo90_Ptsjyzg7po4FYp8s1ZPGHABIqfWhU85PUCHn6w
linkProvider IEEE
linkToHtml http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwzV3NjtMwEB4tywEuLD-LKCzgA1yQ3G0cOz8HDkuXVbv_oq20t2An9gpREtQmQuVdeAOegWdjJnFhBeK4ErcoSuzI-TzzjT2eD-BFUGDQ5VzMVRAZjjNR8DRymjsX2jS1WkjbZvmeRqOZPLxQFxvw7ddZGGttm3xm-3TZ7uUXVd7QUtkuFbEUMhY-h_LIrr5ghLZ8Pd7H3_lSiIO30-GIexEBngsZ1VwnRR4rkzuXWPSWKrFBLouC6uZFVlEB8lwjBUFaL0P0noERNjUyFVpqNyjSIsR2b8BNJBpKdMfDfi_hBMR_Ir9Xih-3ezg-m2LMKVQ_xEhAkibeFW_Xyrf8ZfNbR3awBT_WQ9Dlr3zsN7Xp51__qA75347RXbjjKTTb6zB_DzZseR-21vIUzFurB_B94rX5-Bt01QXbpxrBXt5Lz-cr9q4yzbJmZ2g1P_njqGxi545PFx8uL0nElE1OzocMeT0jYdNWTgNvDlfGLvi5RzjzRd8Z2mBa1GJ1xWYlrVWWbZfNwtDMWjJd4jdQbuOcV457I8326prKHGzD7FrG7CFsllVpHwFLcCJhM9EAybY0KtJaRUmI5AJDc-SHrgev1iDKPnc1SLI2dhukGSEuI8RlHnE92CZQXHmww0MPdta4y7yZWmYhBqRxHKYyfPyP157DrdH05Dg7Hp8ePYHb1BMlygVqBzbrRWOfIiWrzbN2YjB4f90o-wkPI0Sn
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=Security-Based+Distributionally+Robust+Optimization+Self-Triggered+SMPC+for+Constrained+Cyber-Physical+Systems+Subject+to+Unknown+Disturbances+and+Denial-of-Service+Attacks&rft.jtitle=IEEE+internet+of+things+journal&rft.au=Chen%2C+Yadong&rft.au=Cheng%2C+Peng&rft.date=2025-06-15&rft.pub=IEEE&rft.eissn=2327-4662&rft.volume=12&rft.issue=12&rft.spage=21757&rft.epage=21769&rft_id=info:doi/10.1109%2FJIOT.2025.3548405&rft.externalDocID=10912472
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2327-4662&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2327-4662&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2327-4662&client=summon