Evidence map›Paper›PMID 39948116›Full record

ArticleScientific reports2025

A novel fixed-time prescribed performance sliding mode control for uncertain wheeled mobile robots.

Van-Cuong Nguyen, Seong Han Kim

Abstract read
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. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

2 authors.

Van-Cuong NguyenDepartment of Artificial Intelligence and Robotics, Sejong University, Gwangjin-gu, Seoul, 05006, South Korea.
Seong Han KimDepartment of Artificial Intelligence and Robotics, Sejong University, Gwangjin-gu, Seoul, 05006, South Korea. shkim8@sejong.ac.kr.

Funding

Ministry of Science and ICT, South Korea IITP-2024-RS-2022-00156345National Research Foundation of Korea RS-2023-00219051 and RS-2023-00209107
6 · The paper itself

Abstract

This paper proposes a novel fixed-time prescribed performance sliding mode control method, specifically designed to address trajectory tracking issues in wheeled mobile robots (WMRs) affected by wheel slipping, skidding (WSS), and external disturbances. A new prescribed performance sliding surface is first introduced based on a prescribed performance function (PPF) and a non-singular fast terminal sliding function (NFTSF). This design ensures that tracking errors converge to zero within a fixed time while maintaining stability by keeping error states within predefined limits. A novel fixed-time prescribed performance non-singular fast terminal sliding mode control (FPP-NFTSMC) algorithm is proposed based on the sliding function. The control method integrates a uniform second-order sliding mode (USOSM) algorithm to provide a continuous control signal, effectively reducing the chattering effect. This method combines the benefits of PPF, NFTSMC, and USOSM algorithm to achieve high-precision position tracking, minimize chattering, guarantee fixed-time convergence, ensure tracking errors remain within bounds, and maintain robustness against WSS, and external disturbances. The fixed-time stability of the WMR systems is demonstrated by the Lyapunov stability theory. The effectiveness of the proposed method is validated through simulations of tracking straight-line and U-shaped trajectories.

Indexed as

Chattering minimization.Fixed-time sliding mode controlNon-singular fast terminal sliding mode controlPrescribed performance controlUniform second-order sliding mode algorithmWheeled mobile robots

Identifiers

PMID39948116
PMCPMC11825877

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.