The DOI matches its Crossref record; 34 of the 34 references it cites were found in a registry or an index.
Consensus of Hybrid Multi-Agent Systems
Open accessAbstract
In this brief, we consider the consensus problem of hybrid multiagent systems. First, the hybrid multiagent system is proposed, which is composed of continuous-time and discrete-time dynamic agents. Then, three kinds of consensus protocols are presented for the hybrid multiagent system. The analysis tool developed in this brief is based on the matrix theory and graph theory. With different restrictions of the sampling period, some necessary and sufficient conditions are established for solving the consensus of the hybrid multiagent system. The consensus states are also obtained under different protocols. Finally, simulation examples are provided to demonstrate the effectiveness of our theoretical results.
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 4×
“For continuous-time dynamic agents, Olfati-Saber and Murray [17] considered the consensus problem of multi-agent systems with switching topologies and time-delays and obtained some necessary and / or su ffi cient conditions for solving the average consensus.”
InfluentialConsensus 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 1×
“Classic multiagent coordination of interests include consensus [1], flocking [2], containment control [3], formation control [4], coverage control [5], and distributed estimation [6].”
Coordination of groups of mobile autonomous agents using nearest neighbor rules
Jadbabaie, A., Lin, J., & Morse, A. S. (2003) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2003.812781 · Cited by 8,339
Novel Type of Phase Transition in a System of Self-Driven Particles
Vicsek, T., Czirók, A., Ben-Jacob, E., Cohen, I., & Shochet, O. (1995) · Physical Review Letters · doi:10.1103/physrevlett.75.1226 · Cited by 7,380
Consensus seeking in multiagent systems under dynamically changing interaction topologies
Ren, W., & Beard, R. W. (2005) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2005.846556 · Cited by 6,569
Flocking for Multi-Agent Dynamic Systems: Algorithms and Theory
Olfati-Saber, R. (2006) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2005.864190 · Cited by 5,037
Distributed 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
Coverage Control for Mobile Sensing Networks
Cortes, J., Martinez, S., Karatas, T., & Bullo, F. (2004) · IEEE Transactions on Robotics and Automation · doi:10.1109/tra.2004.824698 · Cited by 2,710
Boyd, S., Ghosh, A., Prabhakar, B., & Shah, D. (2006) · IEEE Transactions on Information Theory · doi:10.1109/tit.2006.874516 · Cited by 2,439
On Consensus Algorithms for Double-Integrator Dynamics
Ren, W. (2008) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2008.924961 · Cited by 1,413
Metadata
- Authors
- Zheng, Y., Ma, J., & Wang, L.
- Venue
- IEEE Transactions on Neural Networks and Learning Systems
- Published
- 2018-04
- Volume
- 29
- Issue
- 4
- Pages
- 1359-1365
- ISSN
- 2162-237X (ISSN-L)
- 2162-2388
- OpenAlex
- W2963252619
- Cited by
- 391
- References
- 34
- FWCI
- 37.61
- Type
- journal article
- Language
- en
- Open access
- green
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: Consensus of Hybrid Multi-Agent Systems. https://app.cochat.ai/papers/10.1109/tnnls.2017.2651402
- The paper
- Zheng, Y., Ma, J., & Wang, L. (2018). Consensus of Hybrid Multi-Agent Systems. IEEE Transactions on Neural Networks and Learning Systems. https://doi.org/10.1109/tnnls.2017.2651402
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.