Evidence map›Paper›PMID 41224976›Full record

ArticleScientific reports2025

Predefined-time sliding mode control for position and attitude of quadrotor with variable exponent coefficients.

Lifeng Hou, Jianhua Zhang, Zhanyang Yu, Xinxin Wang, Cheng Siong Chin

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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.

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0citing papers in PubMed
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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

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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

5 authors.

Lifeng HouShijiazhuang College of Applied Technology, Shijiazhuang, 050800, China.
Jianhua ZhangSchool of Information and Control Engineering, Qingdao University of Technology, Qingdao, 266520, China. Jianhuazhang@qut.edu.cn.
Zhanyang YuSchool of Information and Control Engineering, Qingdao University of Technology, Qingdao, 266520, China.
Xinxin WangSchool of Information and Control Engineering, Qingdao University of Technology, Qingdao, 266520, China.
Cheng Siong ChinFaculty of Science, Agriculture, and Engineering, Newcastle University Singapore, Singapore, 599493, Singapore.

Funding

National Natural Science Foundation of China 62203247
6 · The paper itself

Abstract

This paper presents a comprehensive study on predefined-time sliding mode control applied to quadrotor systems with variable exponent coefficients. The main goal is to achieve efficient control with predefined-time convergence to the desired target. Novel predefined-time sliding mode control and predefined-time neural networks sliding model control algorithms are developed to adapt to the dynamics of variable coefficients and ensure system stability. The stability analysis confirms their capability to achieve predefined-time convergence. Extensive numerical simulations on diverse nonlinear systems validate the superiority of the proposed approach over conventional sliding mode control and neural networks control.

Indexed as

Neural networksPredefined-time stabilitySliding mode controlTrajectory tracking

Identifiers

PMID41224976
PMCPMC12612056

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Registered trials

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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.