Multichannel two-gradient direction filtered reference least mean square algorithm for output-constrained multichannel active noise control

Abstract

Multichannel active noise control is a proven and long-standing technique for achieving a large zone of quiet in enclosures and open spaces. In practice, the multichannel active noise control system encounters more significant output saturation nonlinearity than the single-channel system as a result of the increased number of multiple output amplifiers, which not only degrades noise reduction performance but also compromises system stability. Conventional output-saturation solutions are mainly designed for single-channel applications, and their high computational complexity prevents them from being extended to multichannel systems. Hence, this paper proposes a novel two-gradient direction multichannel filtered reference least mean square (FxLMS) method that effectively avoids the saturation problem by restricting the output to the desired range and marginally increasing the computation over the conventional Multichannel FxLMS algorithm. In addition, this paper investigates the step sizes of the algorithm and proposes a computation-efficient variable step-size strategy to reduce further the steady-state error caused by the varying gradient directions. Finally, the efficacy of the proposed algorithm is demonstrated through numerical simulations using measured primary and secondary paths.