FUZZY SETS AND SYSTEMS - Journal - Bridge of Knowledge

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FUZZY SETS AND SYSTEMS

ISSN:

0165-0114

eISSN:

1872-6801

Disciplines
(Field of Science):

  • automation, electronics, electrical engineering and space technologies (Engineering and Technology)
  • information and communication technology (Engineering and Technology)
  • safety engineering (Engineering and Technology)
  • biomedical engineering (Engineering and Technology)
  • economics and finance (Social studies)
  • management and quality studies (Social studies)
  • international relations (Social studies)
  • mathematics (Natural sciences)

Ministry points: Help

Ministry points - current year
Year Points List
Year 2025 140 Ministry scored journals list 2024
Ministry points - previous years
Year Points List
2025 140 Ministry scored journals list 2024
2024 140 Ministry scored journals list 2024
2023 140 Ministry Scored Journals List
2022 140 Ministry Scored Journals List 2019-2022
2021 140 Ministry Scored Journals List 2019-2022
2020 140 Ministry Scored Journals List 2019-2022
2019 140 Ministry Scored Journals List 2019-2022
2018 40 A
2017 40 A
2016 40 A
2015 40 A
2014 40 A
2013 40 A
2012 40 A
2011 40 A
2010 32 A

Model:

Hybrid

Points CiteScore:

Points CiteScore - current year
Year Points
Year 2023 6.5
Points CiteScore - previous years
Year Points
2023 6.5
2022 7.3
2021 7.1
2020 7
2019 6.5
2018 6.6
2017 5.4
2016 4.6
2015 4.3
2014 4.5
2013 4.8
2012 5.6
2011 5.1

Impact Factor:

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Sherpa Romeo:

https://v2.sherpa.ac.uk/id/publication/11428

Papers published in journal

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total: 2

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  • Year

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Catalog Journals

Year 2008
  • Stable indirect adaptive control based on discrete-time T-S fuzzy model
    Publication

    - FUZZY SETS AND SYSTEMS - Year 2008

    This paper presents an indirect adaptive fuzzy control scheme for uncertain nonlinear asymptotically stable plants.A discrete-time T-S fuzzy input-output model is employed to approximate the unknown plant dynamics. The T-S fuzzy model is fed with its own states, which are indeed its past outputs, rather than the measurements from the plants. Entirely based on this model, a feedback linearization control law is designed by using...

    Full text to download in external service

Year 2007
  • Stable indirect adaptive control based on discrete-time T-S fuzzy model
    Publication

    - FUZZY SETS AND SYSTEMS - Year 2007

    This paper presents an indirect adaptive fuzzy control scheme for uncertain nonlinear asymptotically stable plants.A discrete-time T-S fuzzy input-output model is employed to approximate the unknown plant dynamics. The T-S fuzzy model is fed with its own states, which are indeed its past outputs, rather than the measurements from the plants. Entirely based on this model, a feedback linearization control law is designed by using...

    Full text to download in external service

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