Active vibration isolation of a monostable nonlinear electromagnetic actuator using machine learning adaptive feedforward control

Kai Yang, Weihao Tong, Xu Zhou, Ruohan Li, Tingting Zhang, Daniil Yurchenko and Yucheng Shu

Chaos, Solitons & Fractals, 2025, vol. 192, issue C

Abstract: In the realm of nonlinear vibration systems, the control of periodic low-frequency vibrations presents a formidable challenge due to the intricate nature of nonlinear dynamics. This paper proposes a novel machine learning adaptive feedforward active control method tailored for suppressing periodic low-frequency vibrations. Leveraging a monostable nonlinear electromagnetic actuator with an elastic boundary (MAEB), our method harnesses the power of a back-propagation neural network (BPNN) to accurately identify the driving model of the MAEB. This model is then integrated into the adaptive control loop for continuous parameter updating of the controller BPNN. Our approach demonstrates high proficiency in eliminating harmonic frequency components and ensuring robust control stability, thereby surpassing traditional filtered-x least mean square (Fx-LMS) algorithm. Specifically, our approach enhances overall vibration isolation performance by an impressive 7.13 dB compared to the Fx-LMS algorithm. Furthermore, our study validates the efficacy of the proposed method in accommodating variations in excitation, including low-frequency single-line and dual-line spectrums. A detailed parametric study underscores the pivotal role of neural network hyperparameters in enhancing active control performance, with adjustments to the number of hidden layer nodes and the learning rate offering notable improvements in convergence speed.

Keywords: Active vibration control; Adaptive feedforward control; Machine learning; Monostable; Nonlinear actuator (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960077925000487
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:192:y:2025:i:c:s0960077925000487

DOI: 10.1016/j.chaos.2025.116035

Access Statistics for this article

Chaos, Solitons & Fractals is currently edited by Stefano Boccaletti and Stelios Bekiros

More articles in Chaos, Solitons & Fractals from Elsevier
Bibliographic data for series maintained by Thayer, Thomas R. ().