Preventing output saturation in active noise control: An output-constrained Kalman filter approach

TL;DR

This paper introduces an output-constrained Kalman filter for active noise control that prevents output saturation in high-noise environments, ensuring system stability while maintaining rapid noise suppression.

Contribution

A novel output-constrained Kalman filter method is proposed to prevent saturation in active noise control systems, improving stability without sacrificing noise cancellation performance.

Findings

Effective suppression of dynamic noise

Prevents non-linearity due to output saturation

Ensures stability in high-noise environments

Abstract

The Kalman filter (KF)-based active noise control (ANC) system demonstrates superior tracking and faster convergence compared to the least mean square (LMS) method, particularly in dynamic noise cancellation scenarios. However, in environments with extremely high noise levels, the power of the control signal can exceed the system's rated output power due to hardware limitations, leading to output saturation and subsequent non-linearity. To mitigate this issue, a modified KF with an output constraint is proposed. In this approach, the disturbance treated as an measurement is re-scaled by a constraint factor, which is determined by the system's rated power, the secondary path gain, and the disturbance power. As a result, the output power of the system, i.e. the control signal, is indirectly constrained within the maximum output of the system, ensuring stability. Simulation results indicate that the proposed algorithm not only achieves rapid suppression of dynamic noise but also effectively prevents non-linearity due to output saturation, highlighting its practical significance.