MATLAB Convergence Study and Reproducibility Data for Two-Weight Narrowband FxLMS Active Vibration Control Using a Voice-Coil Motor
Description
This dataset accompanies the manuscript “Real-Time Experimental Study of Two-Weight Narrowband FxLMS Active Vibration Control Using a Voice-Coil Motor.” The package provides a numerical convergence and implementation audit of the two-weight narrowband filtered-x least-mean-square (FxLMS) controller examined experimentally in the associated article. It contains a reader-guided MATLAB Live Script, an equivalent plain MATLAB script, machine-readable CSV results, a complete MATLAB results file, generated figures, documentation, and file-integrity checksums. The study covers acceleration-to-voltage command mapping, sinusoidal basis and normalization checks, multitone FxNLMS control, matched-frequency convergence, sign-convention consistency, step-size selection, secondary-path phase error, FxLMS and FxNLMS frequency dependence, controller-frequency mismatch, secondary-path sensitivity, Monte Carlo robustness, and recovery after simulated hammer-strike disturbances. The secondary-path models and structural parameters used in the convergence study are explicitly declared simulation assumptions. Accordingly, the package complements the experimental results but should not be interpreted as a hardware-identified stability proof or as a universal FxLMS stability boundary. A legacy mixed-sign reproduction is included only as a sign-convention diagnostic and not as valid convergence evidence. The package was tested using MATLAB R2020a on 64-bit Windows and does not require a specialized MATLAB toolbox. Additional experimental measurements and the LabVIEW programs used for the real-time implementation are not included in this dataset but may be obtained from the corresponding author upon reasonable request.
Files
Steps to reproduce
Follow the readme file.
Institutions
- Beihang UniversityBeijing, Beijing
Categories
Funders
- China Scholarship CouncilMinistry of Education of the People's Republic of ChinaBeijingGrant ID: 2024GSP007924