Active disturbance rejection control for reducing vehicle body displacement based on an extended state observer and dynamic fuzzy techniques

This article presents a hybrid control method for an automotive suspension system to improve smoothness and comfort and eliminate the influence of sensor noise. The proposed algorithm is formed by combining an active disturbance rejection control technique and a dynamic fuzzy technique based on an e...

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Bibliographic Details
Published in:Journal of low frequency noise, vibration, and active control Vol. 44; no. 2; pp. 1256 - 1271
Main Author: Nguyen, Tuan Anh
Format: Journal Article
Language:English
Published: London, England SAGE Publications 01.06.2025
Sage Publications Ltd
SAGE Publishing
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ISSN:1461-3484, 2048-4046
Online Access:Get full text
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Summary:This article presents a hybrid control method for an automotive suspension system to improve smoothness and comfort and eliminate the influence of sensor noise. The proposed algorithm is formed by combining an active disturbance rejection control technique and a dynamic fuzzy technique based on an extended state observer. The article’s novel contribution is to propose a solution for determining a reference signal and adjusting control parameters using soft computing techniques. Simulations are performed in three cases (corresponding to three types of road excitation signals) to validate the performance of the proposed algorithm. According to the calculation results, the displacement and acceleration of the vehicle body are significantly reduced when the proposed technique is applied to control the active suspension system. The error of the road disturbance observed by the extended state observer does not exceed 0.5 mm, while the error of the vehicle body displacement is less than 0.001 mm. In addition, the chattering phenomenon caused by sensor noise is completely eliminated once the proposed algorithm controls the active suspension system. In conclusion, the algorithm introduced in this work provides superior performance over traditional control methods, which is validated by simulation results.
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ISSN:1461-3484
2048-4046
DOI:10.1177/14613484251315522