Multi-frequency micro-vibration control with hybrid adaptive control algorithm

Y Fang, X Zhu, J Hu, Z Gao… - Transactions of the …, 2020 - journals.sagepub.com
Y Fang, X Zhu, J Hu, Z Gao, H Zhang
Transactions of the Institute of Measurement and Control, 2020journals.sagepub.com
As a popular adaptive algorithm for active vibration control (AVC), filtered-x least mean
square (FxLMS) algorithm sometimes fails to suppress multiple narrowband disturbance. To
control multi-frequency structure vibration, parallel-form FxLMS algorithm can be employed.
However, the conventional parallel-form FxLMS does not perform well in the situation of
disturbance frequency mismatch and wideband measurement noise. For this issue, the
majority of the improvement approaches are based on adaptive frequency estimator. It …
As a popular adaptive algorithm for active vibration control (AVC), filtered-x least mean square (FxLMS) algorithm sometimes fails to suppress multiple narrowband disturbance. To control multi-frequency structure vibration, parallel-form FxLMS algorithm can be employed. However, the conventional parallel-form FxLMS does not perform well in the situation of disturbance frequency mismatch and wideband measurement noise. For this issue, the majority of the improvement approaches are based on adaptive frequency estimator. It increased the computational burden of the parallel-form FxLMS algorithm. Therefore, taking the advantage of feedback control, a hybrid adaptive control for AVC is proposed in this paper. And the “posterior” residual error is adopted for better robustness. The convergence analysis of the hybrid AVC algorithm is given. Co-simulations with ADAMS and SIMULINK are implemented to verify the effectiveness in micro-vibration control system. Some comparison experiments are implemented in a micro-vibration AVC experimental system for several typical disturbances. Experimental results confirm the feasibility and effectiveness of the proposed algorithm.
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