Evidence map›Paper›PMID 35590095›Full record

ArticleScientific reports2022

Distributed adaptive fixed-time neural networks control for nonaffine nonlinear multiagent systems.

Yang Li, Quanmin Zhu, Jianhua Zhang

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.2field-weighted citation impact, top 22% of its field
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

3 citing papers in PubMed, 10 citations in OpenAlex.

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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

3 authors at 2 institutions in 2 countries.

Yang LiSchool of Information and Control Engineering, Qingdao University of Technology, Qingdao, 266525, China.
Quanmin ZhuDepartment of Engineering Design and Mathematics, University of the West of England, Coldharbour Lane, Bristol, BS16 1QY, UK.
Jianhua ZhangSchool of Information and Control Engineering, Qingdao University of Technology, Qingdao, 266525, China. jianhuazhang@qut.edu.cn.
Qingdao University of Technology · CNUniversity of the West of England · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper, with the adaptive backstepping technique, presents a novel fixed-time neural networks leader-follower consensus tracking control scheme for a class of nonaffine nonlinear multiagent systems. The expression of the error system is derived, based on homeomorphism mapping theory, to formulate a set of distributed adaptive backstepping neural networks controllers. The weights of the neural networks controllers are trained, by an adaptive law based on fixed-time theory, to determine the adaptive control input. The control algorithm can guarantee that the output of the follower agents of the system effectively follow the output of the leader of the system in a fixed time, while the upper bound of the settling time can be calculated without initial parameters. Finally, a simulation example is presented to demonstrate the effectiveness of the proposed consensus tracking control approach. A step-by-step procedure for engineers and researchers interested in applications is proposed.

Indexed as

Neural Networks, ComputerNonlinear DynamicsAlgorithmsComputer Simulation

Identifiers

PMID35590095
PMCPMC9120193
OpenAlexW4280576781

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.