Adaptive active vibration control (AAVC) is an effective way for reducing structure vibration at low frequency. AAVC methodology is preferred in AVC system due to its self-adjustment ability to adapt to varying dynamics of the structure. The Filtered-X Least Mean Square (FXLMS) algorithm is widely implemented in active control applications. Accurate secondary path models are very crucial for the implementation in multichannel AAVC system based on FXLMS algorithm. The auxiliary random noise technique is often applied to achieve secondary path modeling (SPM) during online operation. This paper proposes a new multichannel AAVC methodology based on online SPM method. The online SPM error is estimated indirectly to reduce the interaction between the AAVC controller and the online SPM filter. A new variable step-size (VSS) strategy for online SPM filter is proposed based on the estimated online SPM error. A simple but effective auxiliary noise power scheduling (ANPS) method is proposed to eliminate the contribution of the auxiliary noise on the residual vibration. A series of multi-channel AAVC experiments on a cantilever epoxy resin plate with PZT sensors and actuators are presented to demonstrate the performance of the proposed methodology. Experiment results indicate that the proposed method provides very good online SPM accuracy, and the vibration of the smart cantilever plate has been effectively attenuated with high convergence rate.
PERFORMANCE ANALYSIS AND DESIGN OF AUTOMOBILE RADIATOR
