A New Proportionate Filtered-x RLS Algorithm for Active Noise Control System

Abstract

The filtered-x recursive least square (FxRLS) algorithm is widely used in the active noise control system and has achieved great success in some complex de-noising environments, such as the cabin in vehicles and aircraft. However, its performance is sensitive to some user-defined parameters such as the forgetting factor and initial gain. Once these parameters are not selected properly, the de-noising effect of FxRLS will deteriorate. Moreover, the tracking performance of FxRLS for mutation is still restricted to a certain extent. To solve the above problems, this paper proposes a new proportional FxRLS (PFxRLS) algorithm. The forgetting factor and initial gain sensitivity are successfully reduced without introducing new turning parameters. The de-noising level and tracking performance have also been improved. Moreover, the momentum technique is introduced in PFxRLS to further improve its robustness and de-noising level. To ensure stability, its convergence condition is also discussed in this paper. The effectiveness of the proposed algorithms is illustrated by simulations and experiments with different user-defined parameters and time-varying noise environments.

Active Control based on Adaptive Filters for Elastic Supported Cylinders

“…Online modeling of secondary pathways, variable step sizes determined with the FxLMS controller showed improved adaptive control performance over definite time variations (Fallah, 2019). Analysis of several properties of observer-based control robustness and adaptive FxLMS for active control of engine-induced vibration in automotive vehicles (Liang, 2022). In addition, FxNLMS controller feedback can dampen drill rod vibrations of 70 dB for a depth of 0.2 m on 6063-T6 Aluminum alloy material (Wenchao, 2019).…”

Active vibration hybrid control strategy based on multi-DOFs piezoelectric platform

“…Due to the limitation of iterative method and step factor, Fx-LMS algorithm is difficult to reduce the steady-state error and increase the convergence rate in some applications. To overcome the limitation, Liang et al (2022) proposed a new proportional Fx-RLS algorithm, and the forgetting factor and initial gain sensitivity are successfully reduced without introducing new parameters. The feedback control can be used to isolate the interference of the payload, and the feedforward control can be used to offset the impact of floor vibration, which minimizes the amplification of noise and optimizes the vibration isolation performance of the single-input single-out (SISO) system (Beijen et al, 2019).…”