The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Distributed Consensus Tracking for Multiple Uncertain Nonlinear Strict-Feedback Systems Under a Directed Graph
Abstract
In this brief, we study the distributed consensus tracking control problem for multiple strict-feedback systems with unknown nonlinearities under a directed graph topology. It is assumed that the leader's output is time-varying and has been accessed by only a small fraction of followers in a group. The distributed dynamic surface design approach is proposed to design local consensus controllers in order to guarantee the consensus tracking between the followers and the leader. The function approximation technique using neural networks is employed to compensate unknown nonlinear terms induced from the controller design procedure. From the Lyapunov stability theorem, it is shown that the consensus errors are cooperatively semiglobally uniformly ultimately bounded and converge to an adjustable neighborhood of the origin.
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.
Integrity signals
Registry
Cites
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.
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
Consensus Problems in Networks of Agents With Switching Topology and Time-Delays
Olfati-Saber, R., & Murray, R. M. (2004) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2004.834113 · Cited by 12,788 · cited 1×
“Even consensus results on the time delays and switching topology were limited to single-integrator or double-integrator systems [7]–[10].”
BackgroundConsensus and Cooperation in Networked Multi-Agent Systems
Olfati-Saber, R., Fax, J. A., & Murray, R. M. (2007) · Proceedings of the IEEE · doi:10.1109/jproc.2006.887293 · Cited by 10,522 · cited 2×
“3) Compared with the previous consensus works [1]–[25], this brief considers the consensus problem of a group of agents consisting of nonlinear followers with nonlinearities unmatched in the control input.”
BackgroundDistributed Consensus in Multi-vehicle Cooperative Control
Ren, W., & Beard, R. W. (2008) · Communications and Control Engineering · doi:10.1007/978-1-84800-015-5 · Cited by 2,826
Cited by
Wang, W., Wen, C., & Huang, J. (2017) · Automatica · doi:10.1016/j.automatica.2016.11.019 · Cited by 408
Metadata
- Authors
- Yoo, S. J.
- Venue
- IEEE Transactions on Neural Networks and Learning Systems
- Published
- 2013-04
- Volume
- 24
- Issue
- 4
- Pages
- 666-672
- ISSN
- 2162-237X (ISSN-L)
- 2162-2388
- OpenAlex
- W2104708700
- Cited by
- 285
- References
- 3
- FWCI
- 20.27
- Type
- journal article
- Language
- en
- Open access
- closed
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Distributed Consensus Tracking for Multiple Uncertain Nonlinear Strict-Feedback Systems Under a Directed Graph. https://app.cochat.ai/papers/10.1109/tnnls.2013.2238554
- The paper
- Yoo, S. J. (2013). Distributed Consensus Tracking for Multiple Uncertain Nonlinear Strict-Feedback Systems Under a Directed Graph. IEEE Transactions on Neural Networks and Learning Systems. https://doi.org/10.1109/tnnls.2013.2238554
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.
