A new variable step size LMS algorithm-based method for improved online secondary path modeling in active noise control systems

Abstract

Abstract-This paper proposes a new method for online secondary path modeling in active noise control systems. The existing methods for active noise control systems with online secondary path modeling consist of three adaptive filters. The main feature of the proposed method is that it uses only two adaptive filters. In the proposed method, the modified-FxLMS (MFxLMS) algorithm is used in adapting the noise control filter and a new variable step size (VSS) least mean square (LMS) algorithm is proposed for adaptation of the secondary path modeling filter. This VSS LMS algorithm is different from the normalized-LMS (NLMS) algorithm, where the step size is varied in accordance with the power of the reference signal. Here, on the other hand, the step size is varied in accordance with the power of the disturbance signal in the desired response of the modeling filter. The basic idea of the proposed VSS algorithm stems from the fact that the disturbance signal in the desired response of the modeling filter is decreasing in nature, (ideally) converging to zero. Hence, a small step size is used initially and later its value is increased accordingly. The disturbance signal, however, is not available directly, and we propose an indirect method to track its variations. Computer simulations show that the proposed method gives better performance than the existing methods. This improved performance is achieved at the cost of a slightly increased computational complexity.Index Terms-Active noise control, FxLMS algorithm, modified FxLMS algorithm, online secondary path modeling, variable step size least mean square (VSS LMS) algorithm.

Noise power scheduling in active noise control systems with online secondary path modeling

“…A simple analysis shows that ρ(0) ≈ 1 and lim n→∞ ρ(n) → 0 [7]. Now the step size forŜ(z) is calculated as:…”

“…In [7] we have proposed a two-adaptive-filter-based method for OSPM in ANC systems. Here we modify this method and propose using a variablepower additive random noise in the OSPM filter.…”

Multiple Iteration of Weight Updates for Least Mean Square Adaptive Filter in Active Noise Control Application

“…However, the performance of signal convergence in terms of the speed of filter adaptation and the excess of mean square error (MSE) is usually overlooked, which can be critical in a time time-varying environment [2], [3]. Research being carried out to improve the error convergence time of LMS-based algorithm however increased the algorithm complexity [7]- [9] and consequently, implementations are mostly evaluated successfully in a purely simulated domain [10]- [12].…”

A New Online Secondary Path Modeling Method with An Auxiliary Noise Power Scheduling Strategy for Narrowband Active Noise Control Systems

“…The use of auxiliary noise power injection with fixed power was originally proposed by Eriksson [14]. The original idea of Eriksson's method was later modified and extended in [15][16][17][18][19], which used fixed power auxiliary noise in all operating situations. Nevertheless, the fixed power auxiliary noise contributes to the residual error, which we want to minimize, and leads to the performance degradation of the ANC system in the steady state.…”