Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 5

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

An adaptive event‐triggered H∞control framework for nonlinear networked control systems with dual‐channel quantization

Liu, Chongzhi, Tang, Xiaojun, Lu, Youshui, Wen, Guangrui, Zhang, Zhifen, Peng, Jingbo·2024·Asian Journal of Control

Abstract

Networked control system (NCS) is widely used in various fields, but the nonlinear of the controlled plants and the limited network bandwidth bring stability issues, which will affect the performance or even instability of the NCS. To address these aforementioned challenges, this paper proposes a novel nonlinear NCS framework, by considering network‐induced delay, adaptive event‐triggered mechanism, state quantization, control input quantization, and external disturbance based on T‐S fuzzy model. Also, based on this framework, we derive an stability criterion for NCS using linear matrix inequality and propose a collaborative design method for event triggers and controllers. Finally, we verify the superiority and effectiveness of the method by giving two numerical examples.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1002/asjc.3290

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Research works printed but not linked: 43

  1. 10.1016/j.automatica.2018.01.026 · DOI
  2. 10.1016/j.jsv.2016.01.008 · DOI
  3. 10.1002/asjc.3045 · DOI
  4. 10.1016/j.ins.2015.07.047 · DOI
  5. 10.1109/TII.2015.2506545 · DOI
  6. 10.1109/37.898794 · DOI
  7. 10.1109/JAS.2019.1911651 · DOI
  8. 10.1016/S0005-1098(03)00196-1 · DOI
  9. H.Lin G.Zhai andP.Antsaklis Robust stability and disturbance attenuation analysis of a class of networked control systems Proc. Conf. Decis. Control IEEE Maui Hawaii 2003 pp.1182–1187. · DOI
  10. 10.1016/j.automatica.2004.12.011 · DOI
  11. 10.1109/TFUZZ.2017.2764851 · DOI
  12. 10.1016/j.automatica.2016.02.006 · DOI
  13. Song J., 2020, H∞$$ {H}_{\infty } $$ controller design of networked control systems with a new quantization structure, Appl. Math. Comput., 376, 0096
  14. Chen S., 2020, Event‐triggered control for networked systems with time‐delay and quantization, 207
  15. 10.1002/asjc.2191 · DOI
  16. 10.1002/asjc.2524 · DOI
  17. 10.1002/asjc.2772 · DOI
  18. 10.1109/TAC.2007.904277 · DOI
  19. 10.1109/TAC.2012.2206694 · DOI
  20. 10.1002/asjc.2810 · DOI
  21. 10.1002/asjc.3054 · DOI
  22. 10.1002/asjc.3056 · DOI
  23. 10.1002/asjc.2503 · DOI
  24. 10.1109/TSMC.2019.2918547 · DOI
  25. X.RenandF.Hao Event‐triggered stability of singularly perturbed system with time delay 2020 39th Chin. Control Conf. (CCC) IEEE Shenyang China 2020 pp.112–117. · DOI
  26. 10.1016/j.jfranklin.2020.01.019 · DOI
  27. 10.1080/00207179.2021.1876924 · DOI
  28. 10.1109/TNNLS.2022.3210269 · DOI
  29. 10.1109/TSMC.1985.6313399 · DOI
  30. 10.1109/TSMC.2016.2614779 · DOI
  31. 10.1002/rnc.6501 · DOI
  32. 10.1007/s00500-022-07205-6 · DOI
  33. 10.1007/s00521-020-04826-6 · DOI
  34. 10.1109/TFUZZ.2019.2955054 · DOI
  35. Zhu X. L., 2009, New H∞$$ {H}_{\infty } $$ controller design method for networked control systems with quantized state feedback, 2009 American Control Conference, 5103
  36. 10.1109/TIE.2015.2475515 · DOI
  37. 10.1016/j.isatra.2011.09.002 · DOI
  38. 10.1016/j.ins.2017.09.005 · DOI
  39. 10.1002/rnc.3273 · DOI
  40. Y. J.Pan H. J.Marquez andT.Chen Sampled‐data iterative learning control for a class of nonlinear networked control systems 2006 Amer. Control Conf. IEEE Minneapolis MN 2006.
  41. 10.1109/TSMCB.2008.2007496 · DOI
  42. T.LiuandX.Liu Stability criterion for networked control systems based on T‐S model with time‐varying delays 2018 IEEE 7th Data Driven Control Learn. Syst. Conf. (DDCLS) IEEE Enshi China 2018 pp.1085–1088. · DOI
  43. Deng W.‐H., 2010, T‐S fuzzy H∞$$ {H}_{\infty } $$ control and numerical simulation of nonlinear networked control systems, J. Syst. Simul., 22, 1651

Metadata

Authors
Liu, C., Tang, X., Lu, Y., Wen, G., Zhang, Z., & Peng, J.
Venue
Asian Journal of Control
Publisher
Wiley
Published
2023-12-17
Volume
26
Issue
4
Pages
1734-1748
ISSN
  • 1561-8625
  • 1934-6093
Cited by
5
References
1
Language
en
Funders
National Science and Technology Major Project (J2019‐V‐0003‐0094)

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.