The DOI matches its Crossref record.
Platoon Formation Control With Prescribed Performance Guarantees for USVs
Abstract
This paper studies the platoon formation control problem for unmanned surface vehicles, in the presence of modeling uncertainties and time-varying external disturbances. The control objective is to make the vehicular platoons proceed along a given trajectory while maintaining a desired line-of-sight (LOS) range between each vehicle and its predecessor. To provide transient performance specifications on formation errors, including LOS range and angle errors, we enforce prescribed performance guarantees in the control design. The prescribed performance guarantees mean that formation errors evolve always within the predefined regions that are bounded by exponentially decaying functions of time. Using prescribed performance control methodology, neural network approximation, disturbance observers, dynamic surface control technique, and Lyapunov synthesis, we propose an adaptive formation control that ensures internal stability of closed-loop systems with guaranteed prescribed performance. Meanwhile, both collision avoidance and connectivity maintenance between two consecutive vehicles are guaranteed during the whole operation. The proposed formation control is decentralized in the sense that the control action on each vehicle depends only on information from its immediate predecessor. Simulation results demonstrate the performance of the proposed control.
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
Cited by
An Overview of Recent Advances in Coordinated Control of Multiple Autonomous Surface Vehicles
Peng, Z., Wang, J., Wang, D., & Han, Q.-L. (2021) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2020.3004343 · Cited by 757
Reinforcement learning-based optimal tracking control of an unknown unmanned surface vehicle
Wang, N., Gao, Y., Zhao, H., & Ahn, C. K. (2021) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2020.3009214 · Cited by 322
Adaptive Neural Control of Underactuated Surface Vessels With Prescribed Performance Guarantees
Dai, S.-L., He, S., Wang, M., & Yuan, C. (2019) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2018.2876685 · Cited by 320
Self-citationAdvances in Line-of-Sight Guidance for Path Following of Autonomous Marine Vehicles: An Overview
Gu, N., Wang, D., Peng, Z., Wang, J., & Han, Q.-L. (2023) · IEEE Transactions on Systems, Man, and Cybernetics: Systems · doi:10.1109/tsmc.2022.3162862 · Cited by 316
Reinforcement Learning Control of a Flexible Two-Link Manipulator: An Experimental Investigation
He, W., Gao, H., Zhou, C., Yang, C., & Li, Z. (2021) · IEEE Transactions on Systems, Man, and Cybernetics: Systems · doi:10.1109/tsmc.2020.2975232 · Cited by 284
Metadata
- Authors
- Dai, S.-L., He, S., Lin, H., & Wang, C.
- Venue
- IEEE Transactions on Industrial Electronics
- Published
- 2018-05
- Volume
- 65
- Issue
- 5
- Pages
- 4237-4246
- ISSN
- 0278-0046 (ISSN-L)
- 1557-9948
- OpenAlex
- W2761264428
- Cited by
- 327
- References
- 0
- FWCI
- 22.20
- 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: Platoon Formation Control With Prescribed Performance Guarantees for USVs. https://app.cochat.ai/papers/10.1109/tie.2017.2758743
- The paper
- Dai, S.-L., He, S., Lin, H., & Wang, C. (2018). Platoon Formation Control With Prescribed Performance Guarantees for USVs. IEEE Transactions on Industrial Electronics. https://doi.org/10.1109/tie.2017.2758743
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.