A variable step-size FxLMS algorithm for active vibration control of cantilever beam
The conventional filtered-x least mean square (FxLMS) algorithm for active vibration control (AVC) is limited by the trade-off between convergence rate and steady-state error and by its sensitivity to abrupt input changes. To address these issues, a nonlinear step-size adjustment mechanism combining a bounded hyperbolic tangent mapping with a normalized variable step-size strategy is developed, based on which a variable step-size FxLMS algorithm, termed VSS-FxtanhLMS, is proposed. The convergence properties of the algorithm are analyzed in the mean and mean-square senses. For AVC of a flexible cantilever beam, the proposed algorithm is evaluated on a co-simulation platform established using ADAMS and Simulink under single-frequency, dual-frequency, and amplitude-step excitations, and is further validated on an experimental AVC platform. Co-simulation results show that VSS-FxtanhLMS achieves the smallest steady-state error, the lowest mean squared error, and the shortest convergence time under both single-frequency and dual-frequency excitations, while remaining convergent under amplitude-step excitation. In experiments, compared with FxasinhLMS, the strongest competing method, VSS-FxtanhLMS reduces the steady-state error by 17.48%, shortens the convergence time by 33.33%, and reduces the power spectral density by 1.72 dB/Hz. These results indicate that VSS-FxtanhLMS achieves improved steady-state accuracy, convergence behavior, and robustness under both simulation and practical conditions.
Authors
- Xiaoyan Chen (ORCID: https://orcid.org/0000-0002-0885-2588)
- Jinhua Jiang (ORCID: https://orcid.org/0000-0002-3213-8878)
- Qian Wang (ORCID: https://orcid.org/0000-0001-6851-0005)
- Zimei Tu
- Yihan Yan
Institutions
- Shanghai Polytechnic University (CN)
Publication Details
- Journal
- Journal of low frequency noise, vibration and active control
- Published
- 2026-07-17
- DOI
- https://doi.org/10.1177/14613484261470208
- Primary Topic
- Advanced Adaptive Filtering Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00