Practical Active Noise Control: Restriction of Maximum Output Power

TL;DR

This paper introduces recent algorithms for real-time adaptive active noise control that effectively handle challenges like speaker saturation, system divergence, and disturbance rejection, improving noise reduction performance.

Contribution

The paper presents novel algorithms that enhance the stability and robustness of active noise control systems in real-time applications.

Findings

Algorithms effectively mitigate speaker saturation effects.

Improved disturbance rejection capabilities.

Guidelines for implementing robust AANC systems.

Abstract

This paper presents some recent algorithms developed by the authors for real-time adaptive active noise (AANC) control systems. These algorithms address some of the common challenges faced by AANC systems, such as speaker saturation, system divergence, and disturbance rejection. Speaker saturation can introduce nonlinearity into the adaptive system and degrade the noise reduction performance. System divergence can occur when the secondary speaker units are over-amplified or when there is a disturbance other than the noise to be controlled. Disturbance rejection is important to prevent the adaptive system from adapting to unwanted signals. The paper provides guidelines for implementing and operating real-time AANC systems based on these algorithms.