Active noise control techniques for nonlinear systems

TL;DR

This paper reviews recent advances in nonlinear active noise control (NLANC) algorithms, highlighting new methods like spline and kernel adaptive filters, and discusses their applications and future challenges.

Contribution

It provides a comprehensive review of the development and recent progress of NLANC algorithms over the past decade, including heuristic and advanced nonlinear techniques.

Findings

Recent NLANC algorithms include spline and kernel adaptive filters.

NLANC techniques have been successfully applied in various practical scenarios.

Future challenges in NLANC research are identified and discussed.

Abstract

Most of the literature focuses on the development of the linear active noise control (ANC) techniques. However, ANC systems might have to deal with some nonlinear components and the performance of linear ANC techniques may degrade in this scenario. To overcome this limitation, nonlinear ANC (NLANC) algorithms were developed. In Part II, we review the development of NLANC algorithms during the last decade. The contributions of heuristic ANC algorithms are outlined. Moreover, we emphasize recent advances of NLANC algorithms, such as spline ANC algorithms, kernel adaptive filters, and nonlinear distributed ANC algorithms. Then, we present recent applications of ANC technique including linear and nonlinear perspectives. Future research challenges regarding ANC techniques are also discussed.