View in EDS

Adaptive non‐linear trajectory tracking control for lane change of autonomous four‐wheel independently drive electric vehicles.

Saved in:
Bibliographic Details
Title: Adaptive non‐linear trajectory tracking control for lane change of autonomous four‐wheel independently drive electric vehicles.
Authors: Guo, Jinghua, Luo, Yugong, Li, Keqiang
Source: IET Intelligent Transport Systems (Wiley-Blackwell); Sep2018, Vol. 12 Issue 7, p712-720, 9p
Subject Terms: VEHICULAR ad hoc networks, BACKSTEPPING control method, LANE changing, ADAPTIVE control systems, LATERAL loads
Abstract: Since autonomous four‐wheel independently drive electric vehicles have the characteristics of parameter uncertainties, non‐linearities and redundant actuators, trajectory tracking control for lane change of autonomous electric vehicles is regarded as a challenging task. A novel non‐linear trajectory tracking control strategy is designed for lane changing manoeuvre. First, a dynamic trajectory planning strategy is proposed to update the desired trajectory according to the real‐time information acquired through vehicle‐to‐vehicle communications. Second, a robust adaptive non‐linear fuzzy backstepping controller is presented to produce the generalised forces/moment of autonomous electric vehicles, and the stability of this proposed adaptive controller is proven by the Lyapunov theory. Then, the quadratic optimisation goal function of tire energy dissipated power is constructed, and the optimal control allocation method is proposed to produce the desired longitudinal and lateral tire forces of autonomous electric vehicles. Finally, simulation results manifest that the proposed adaptive control strategy has the distinguished tracking performance. [ABSTRACT FROM AUTHOR]
Copyright of IET Intelligent Transport Systems (Wiley-Blackwell) is the property of Wiley-Blackwell 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=1751956X&ISBN=&volume=12&issue=7&date=20180901&spage=712&pages=712-720&title=IET Intelligent Transport Systems (Wiley-Blackwell)&atitle=Adaptive%20non%E2%80%90linear%20trajectory%20tracking%20control%20for%20lane%20change%20of%20autonomous%20four%E2%80%90wheel%20independently%20drive%20electric%20vehicles.&aulast=Guo%2C%20Jinghua&id=DOI:10.1049/iet-its.2017.0278
    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=Guo%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: 183824728
RelevancyScore: 873
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 873.456176757813
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Adaptive non‐linear trajectory tracking control for lane change of autonomous four‐wheel independently drive electric vehicles.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Guo%2C+Jinghua%22">Guo, Jinghua</searchLink><br /><searchLink fieldCode="AR" term="%22Luo%2C+Yugong%22">Luo, Yugong</searchLink><br /><searchLink fieldCode="AR" term="%22Li%2C+Keqiang%22">Li, Keqiang</searchLink>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: IET Intelligent Transport Systems (Wiley-Blackwell); Sep2018, Vol. 12 Issue 7, p712-720, 9p
– Name: Subject
  Label: Subject Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22VEHICULAR+ad+hoc+networks%22">VEHICULAR ad hoc networks</searchLink><br /><searchLink fieldCode="DE" term="%22BACKSTEPPING+control+method%22">BACKSTEPPING control method</searchLink><br /><searchLink fieldCode="DE" term="%22LANE+changing%22">LANE changing</searchLink><br /><searchLink fieldCode="DE" term="%22ADAPTIVE+control+systems%22">ADAPTIVE control systems</searchLink><br /><searchLink fieldCode="DE" term="%22LATERAL+loads%22">LATERAL loads</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Since autonomous four‐wheel independently drive electric vehicles have the characteristics of parameter uncertainties, non‐linearities and redundant actuators, trajectory tracking control for lane change of autonomous electric vehicles is regarded as a challenging task. A novel non‐linear trajectory tracking control strategy is designed for lane changing manoeuvre. First, a dynamic trajectory planning strategy is proposed to update the desired trajectory according to the real‐time information acquired through vehicle‐to‐vehicle communications. Second, a robust adaptive non‐linear fuzzy backstepping controller is presented to produce the generalised forces/moment of autonomous electric vehicles, and the stability of this proposed adaptive controller is proven by the Lyapunov theory. Then, the quadratic optimisation goal function of tire energy dissipated power is constructed, and the optimal control allocation method is proposed to produce the desired longitudinal and lateral tire forces of autonomous electric vehicles. Finally, simulation results manifest that the proposed adaptive control strategy has the distinguished tracking performance. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label:
  Group: Ab
  Data: <i>Copyright of IET Intelligent Transport Systems (Wiley-Blackwell) is the property of Wiley-Blackwell 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=183824728
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1049/iet-its.2017.0278
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 9
        StartPage: 712
    Subjects:
      – SubjectFull: VEHICULAR ad hoc networks
        Type: general
      – SubjectFull: BACKSTEPPING control method
        Type: general
      – SubjectFull: LANE changing
        Type: general
      – SubjectFull: ADAPTIVE control systems
        Type: general
      – SubjectFull: LATERAL loads
        Type: general
    Titles:
      – TitleFull: Adaptive non‐linear trajectory tracking control for lane change of autonomous four‐wheel independently drive electric vehicles.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Guo, Jinghua
      – PersonEntity:
          Name:
            NameFull: Luo, Yugong
      – PersonEntity:
          Name:
            NameFull: Li, Keqiang
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 09
              Text: Sep2018
              Type: published
              Y: 2018
          Identifiers:
            – Type: issn-print
              Value: 1751956X
          Numbering:
            – Type: volume
              Value: 12
            – Type: issue
              Value: 7
          Titles:
            – TitleFull: IET Intelligent Transport Systems (Wiley-Blackwell)
              Type: main
ResultId 1