Broadband Active Noise Control Based on Interval Type-2 Fuzzy VSS-FxLMS Algorithm

With the development of society, noise pollution has become one of the factors that seriously affect people's daily life. Active Noise Control (ANC) has attracted more and more attention as a low and medium frequency noise reduction technique. For ANC systems, the Filter-x Least Mean Square (FxLMS) algorithm is widely used. However, because of its fixed step size and poor anti-interference performance, it struggles to achieve a steady state performance without compromising convergence speed. At the same time, the noise that widely existed in life, such as the vehicle honking in the traffic field, has the characteristics of wide bandwidth, medium and low frequency, so this paper takes this kind of common noise as the research object, founded on the architecture of a feedforward broadband active noise management system, it using frequency domain analysis to uncover the nonlinear connection between the step size and the frequency features of the noise. Taking into account the uncertainty of the variable step size in FxLMS algorithm model, the interval type-2 fuzzy set is applied for establishing the relationship between the noise frequency and step size. The interval type-2 fuzzy-based variable step size FxLMS algorithm is constructed. According to the simulation experiments in different scenarios, it is verified that the variable step size algorithm based on interval type-2 fuzzy has better noise reduction performance and anti-interference for low and medium frequency noise.