William C. Nowlin

Experimental results for multichannel feedforward ANC with noninvasive system identification

This paper presents experimental validation of a class of algorithms designed to enable active noise control (ANC) to function in environments when transfer functions change significantly over time. The experimental results presented are for broadband, local quieting in a diffuse field using a multichannel ANC system. The reverberant enclosure is an ordinary room, measuring approximately 1.4 x 2.4 x 2.4 m3 and containing a seated occupant, with six microphones defining the quiet zone near the occupants ears. The control system uses a single reference signal and two error channels to drive four secondary sources. Using an ideal reference sensor, reduction in sound pressure level is obtained at the quiet-zone microphones averaged over the frequency range 50 to 1000 Hz with an occupant seated in the room. Two main results are presented: first for an adaptive cancelling algorithm that uses static system models, and second for the same algorithm joined with a noninvasive real-time system identification algorithm. In the first case better than 23 dB of performance is obtained if the occupant remains still through calibration and testing. In the second case, approximately 18 dB is obtained at the error microphones regardless of the motion of the occupant.

Multichannel block adaptive filters for real‐time, nonparametric identification of time‐varying plants

Many real‐world applications of active noise control are characterized by transfer functions that vary significantly and unpredictably. The controller’s transfer function models must adapt to these variations. Presented here is a class of adaptive filters that accomplish quasiperiodic system identification updates for feedforward control by using blocks of input–output histories. The algorithms form a one‐dimensional family linking normalized LMS adaptive filters and optimal Wiener filters, and are termed ‘‘block projection’’ algorithms. The system identification proceeds noninvasively, producing nonparametric (FIR) impulse responses. The multichannel generalization and application of these algorithms to system identification, as presented here, is novel. Considerations are described that arise from the algorithms’ implementation in the context of system identification; in particular, the proper weighting of input and output data pairs is discussed. The resulting multichannel control algorithms have been implemented successfully for quieting of a compact distributed source in an anechoic environment, and for local quieting of a diffuse field in a reverberant room. In both cases, error microphones could be moved about, providing a ‘‘mobile quiet zone,’’ and performance was obtained for bandwidths exceeding a decade.

Attenuation of broadband noise in a reverberant room using a multichannel active noise control system

Active noise control (ANC) is often discussed in the context of reducing noise in vehicles. The acoustic reverberation of typical vehicle cabins makes the application of ANC to quieting interior noise a stiff challenge. While some ANC approaches take advantage of the modal structure of reverberant enclosures to provide reduction throughout the enclosure, these approaches become infeasible for many frequency bands of practical interest because of increasing modal density with increasing frequency. For high‐bandwidth, diffuse fields, noise reduction is achieved locally by specifying a quiet zone within the enclosure. Experimental results for broadband, local quieting in a diffuse field using a multichannel ANC system are presented. The reverberant enclosure is an ordinary room, measuring approximately 1.4 m×2.4 m×2.4 m and containing a seated operator with six microphones defining the quiet zone near the operator’s ears. The control system uses a single reference signal and two error channels to drive four ...