View in EDS

Output feedback robust MPC of uncertain norm-bounded linear systems with disturbance.

Saved in:
Bibliographic Details
Title: Output feedback robust MPC of uncertain norm-bounded linear systems with disturbance.
Authors: Hu, Jianchen, Ding, Baocang
Source: International Journal of Control; Sep2021, Vol. 94 Issue 9, p2388-2395, 8p
Subject Terms: LINEAR systems, PREDICTION models, PROBLEM solving
Abstract: The output feedback robust model predictive control (MPC) for the linear systems with norm-bounded uncertainty and disturbance is studied. A new state estimator is formulated where both estimator dynamic matrix and estimator gain are decision variables being optimised on-line. The infinite horizon control moves are parameterised as a feedback control law, and the resultant non-convex optimisation problem is solved through a linearisation method. The recursive feasibility and closed-loop stability are guaranteed. The proposed approach can achieve better performance and include previous approaches as special cases. Two numerical examples are given to illustrate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Control is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Complementary Index
FullText Text:
  Availability: 0
CustomLinks:
  – Url: https://resolver.ebscohost.com/openurl?sid=EBSCO:edb&genre=article&issn=00207179&ISBN=&volume=94&issue=9&date=20210901&spage=2388&pages=2388-2395&title=International Journal of Control&atitle=Output%20feedback%20robust%20MPC%20of%20uncertain%20norm-bounded%20linear%20systems%20with%20disturbance.&aulast=Hu%2C%20Jianchen&id=DOI:10.1080/00207179.2019.1707290
    Name: Full Text Finder
    Category: fullText
    Text: Full Text Finder
    Icon: https://imageserver.ebscohost.com/branding/images/FTF.gif
    MouseOverText: Full Text Finder
  – Url: https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=EBSCO&SrcAuth=EBSCO&DestApp=WOS&ServiceName=TransferToWoS&DestLinkType=GeneralSearchSummary&Func=Links&author=Hu%20J
    Name: ISI
    Category: fullText
    Text: Nájsť tento článok vo Web of Science
    Icon: https://imagesrvr.epnet.com/ls/20docs.gif
    MouseOverText: Nájsť tento článok vo Web of Science
Header DbId: edb
DbLabel: Complementary Index
An: 151857301
RelevancyScore: 916
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 915.649108886719
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Output feedback robust MPC of uncertain norm-bounded linear systems with disturbance.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Hu%2C+Jianchen%22">Hu, Jianchen</searchLink><br /><searchLink fieldCode="AR" term="%22Ding%2C+Baocang%22">Ding, Baocang</searchLink>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: International Journal of Control; Sep2021, Vol. 94 Issue 9, p2388-2395, 8p
– Name: Subject
  Label: Subject Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22LINEAR+systems%22">LINEAR systems</searchLink><br /><searchLink fieldCode="DE" term="%22PREDICTION+models%22">PREDICTION models</searchLink><br /><searchLink fieldCode="DE" term="%22PROBLEM+solving%22">PROBLEM solving</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: The output feedback robust model predictive control (MPC) for the linear systems with norm-bounded uncertainty and disturbance is studied. A new state estimator is formulated where both estimator dynamic matrix and estimator gain are decision variables being optimised on-line. The infinite horizon control moves are parameterised as a feedback control law, and the resultant non-convex optimisation problem is solved through a linearisation method. The recursive feasibility and closed-loop stability are guaranteed. The proposed approach can achieve better performance and include previous approaches as special cases. Two numerical examples are given to illustrate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of Control is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://erproxy.cvtisr.sk/sfx/access?url=https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edb&AN=151857301
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1080/00207179.2019.1707290
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 8
        StartPage: 2388
    Subjects:
      – SubjectFull: LINEAR systems
        Type: general
      – SubjectFull: PREDICTION models
        Type: general
      – SubjectFull: PROBLEM solving
        Type: general
    Titles:
      – TitleFull: Output feedback robust MPC of uncertain norm-bounded linear systems with disturbance.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Hu, Jianchen
      – PersonEntity:
          Name:
            NameFull: Ding, Baocang
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 09
              Text: Sep2021
              Type: published
              Y: 2021
          Identifiers:
            – Type: issn-print
              Value: 00207179
          Numbering:
            – Type: volume
              Value: 94
            – Type: issue
              Value: 9
          Titles:
            – TitleFull: International Journal of Control
              Type: main
ResultId 1