Evidence map›Paper›PMID 40000777›Full record

ArticleScientific reports2025

Prescribed time reliable platooning control for connected autonomous vehicles using neural network adaptive estimator approach.

Balakrishnan Devanathan, Palanisamy Selvaraj, Arumugam Suyampulingam, Karuppasamy Ilango

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Balakrishnan DevanathanDepartment of Electrical and Electronics Engineering, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Coimbatore, 641112, India.
Palanisamy SelvarajDepartment of Mathematics, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Chennai, 601103, India. p_selvaraj@ch.amrita.edu.
Arumugam SuyampulingamDepartment of Electrical and Electronics Engineering, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Coimbatore, 641112, India. a_suyampulingam@cb.amrita.edu.
Karuppasamy IlangoDepartment of Electrical and Electronics Engineering, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Coimbatore, 641112, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper studied the prescribed-time platooning control problem for connected autonomous vehicles subject to unknown dynamics and stochastic actuator faults. Precisely, to compensate for the effect of unknown dynamic behaviour, the radial basis function-based adaptive observer design was developed that incorporates into the closed-loop control system, which enhances the robustness of the proposed control algorithm. In addition, physical actuator fault factors are also taken into account, which are denoted in terms of a Bernoulli-distributed stochastic variable. Lyapunov stability theory and the stochastic analysis method is used to derive the stability of the addressed control system. Finally, a numerical example with detailed simulation results is provided to illustrate the effectiveness of the proposed control design.

Indexed as

Connected autonomous vehiclePlatooning controlPrescribed-time stabilityRBFNN-based adaptive observerStochastic actuator faultsString stability

Identifiers

PMID40000777
PMCPMC11862195

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.