A Study On Adaptive Active Noise Control Algorithm

Compare with the passive noise control,the active noise control technology are more efficient for lower frequency noise.For better noise control effect,the active control section and the modeling of secondary path section of the feedforward active noise control algorithm are deeply studied in this paper.Firstly,the modeling method of secondary path is analyzed in this paper,Aim at the problems of the low modeling accuracy of the secondary path and the interaction between modeling signal and control signal for the feedforward active noise control system,an online secondary path modeling algorithm based on gradient descent for active noise control is proposed.The gradient descent method is introduced to adjust the convergence factor in the modeling process.The detection threshold is set for the step size.When the step size reaches the threshold,the gradient is taken to the convergence factor for improving modeling accuracy.The convergence factors of active control section and the modeling section are adjusted respectively with the error energy ratio of the two sections.The interaction of the two convergence factors can be further reduced by adjusting the active control ones according to the changing rule of modeling convergence factors.Then,for noise control section,based on the analysis of normalization least mean square(NLMS)algorithm and variable step size LMS algorithm,considering the large variation of the noise signal energy,a NLMS active noise control algorithm based on variable step size is proposed in this paper(FX-VSSNLMS algorithm).The algorithm uses the square Euclidean norm of the input signal to normalize the convergent factor of the change.When the energy of input signal becomes larger,the modified algorithm can automatically select the small step size,which can avoid the divergence of the algorithm.When the input signal energy becomes smaller,a large step size is selected to improve the convergence speed.This method combines the advantages of "normalization" and "variable step size".It not only has better noise reduction,but also has better robust ability.Finally,the simulation experiments of active noise control are carried out for the two improved algorithms for different noise background.By comparing the two improved algorithms,with the pre improved algorithm,the improvement of the modified algorithm in noise control is displayed.