The Comparison of LMS Based Algorithms for Active Cancellation of Motor Noise

Abstract

In this paper an active noise cancellation system to decrease the motor noise arriving to car driver is proposed. This system can be considered as a feedforward control system since it enables taking motor noise as the reference signal. The coefficients of adaptive filters in this structure are obtained with LMS (Least Mean Square) algorithm. In this study both standard (LMS and normalized LMS) and more advanced (variable tap length LMS and variable step size LMS) LMS algorithms are used and their performances are compared. For the different models belonging to different configurations of the system the acoustic noise simulations which contains real noise signal belonging to motor of an accelerated car are realized. According to the results of these simulations the advanced LMS algorithms are observed to converge more rapidly and have better error performances within whole signal and steady-state as compared to classical algorithms.