Influence of modeling error on noise reduction performance of active noise control systems using filtered-X LMS algorithm.

Abstract

This paper investigates the influence of modeling error that is the difference of the characteristic between the secondary path and its model on the behavior of the filtered-X LMS adaptive filter. The equations that describe the behavior of the adaptive filter are presented at first, and the influence of modeling error is considered based on the equations. Both the stability and the noise reduction performance are discussed, and particularly, we discussed in detail the noise reduction performance under modeling error condition that has rarely been considered. In addition, the conditions required for maintaining the noise reduction performance is also presented. The results of the theoretical consideration are confirmed by computer simulation in which the impulse responses measured in a vehicle cabin are used. Through the investigation, it is proved that the algorithm may be stable except for the substantial modeling error case, and the noise reduction performance will be inferior to that under ideal condition in general. These results suggest that we should use the on-line identification system when the secondary path characteristic is time variant.