Evidence map›Paper›PMID 40493556›Full record

ArticlePloS one2025

Dynamic response force control of electrohydraulic servo actuator of active suspension based on intelligent optimization algorithm.

Qinghe Guo, Mengchao Wang, Renjun Liu, Yurong Chen, Shenghuai Wang, Hongxia Wang

Abstract read
In one paragraph

Article in PloS one, 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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1 · What the graph read from it

What it found

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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

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No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Qinghe GuoSchool of Mechanical Engineering, Hubei University of Automotive Technology, Shiyan, Hubei, China.
Mengchao WangSchool of Mechanical Engineering, Hubei University of Automotive Technology, Shiyan, Hubei, China.
Renjun LiuSchool of Art and Design, Hubei University of Automotive Technology, Shiyan, Hubei, China.ORCID https://orcid.org/0009-0005-7346-7861
Yurong ChenSchool of Mechanical Engineering, Hubei University of Automotive Technology, Shiyan, Hubei, China.
Shenghuai WangSchool of Mechanical Engineering, Hubei University of Automotive Technology, Shiyan, Hubei, China.
Hongxia WangSchool of Mechanical Engineering, Hubei University of Automotive Technology, Shiyan, Hubei, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Traditional PID control faces challenges in addressing parameter uncertainty and nonlinearity in active suspension electrohydraulic servo actuators, leading to suboptimal performance. To address these challenges, a fractional-order PID (FOPID) controller optimization method based on the Multi-Strategy Improved Beluga Whale Optimization (MSIBWO) algorithm is proposed. Simulation results in MATLAB/Simulink demonstrate that the MSIBWO-FOPID controller significantly outperforms traditional PID and BWO-FOPID controllers in force tracking and robustness. For step input, the rise time and the root mean square error(RMSE) are reduced by 66.7[Formula: see text] and 70.3[Formula: see text], respectively, compared to BWO-FOPID. For sine inputs, the system achieves better disturbance rejection and higher precision. Using a half-car model, the MSIBWO-FOPID controller improves ride comfort significantly. Under random road excitation, the RMSE values of the vehicle body's vertical acceleration and pitch angle acceleration are reduced by 51.7[Formula: see text] and 13.1[Formula: see text], respectively, compared to passive suspension, outperforming both PID and BWO-FOPID controllers.

Indexed as

AlgorithmsAnimalsComputer SimulationHumansModels, Theoretical

Identifiers

PMID40493556
PMCPMC12151411

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LicenceCC BY
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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.