Alternative switching hybrid ANC. (February 2021)

• Record Type: Journal Article
• Authors: Shen, Xiaoyi; Gan, Woon-Seng; Shi, Dongyuan
• Is Part Of: Applied acoustics. Volume 173(2021)
• Publication Date: 2021-02
• Subjects: Uncorrelated narrow-band noise -- Hybrid active noise control -- Filter-x least mean square; Acoustical engineering -- Periodicals; Periodicals; 620.2
• DOI: 10.1016/j.apacoust.2020.107712
• Languages: English
• ISSNs: 0003-682X

Abstract

Highlights: Hybrid active noise control structure with switches on feedforward and feedback control filters. Proposed alternative switching hybrid active noise control algorithm has reduced 25% and 45% computational complexity than the conventional hybrid active noise control and cascading hybrid active noise control, while has almost the same convergence speed as the cascading hybrid active noise control, and improved convergence speed than conventional hybrid active noise control. This paper proposes an alternative switching hybrid active noise control algorithm based on the slope of the learning curve, which determines the switch of different states. Abstract: The feedforward active noise control (FF ANC) technique has been widely used to cancel the broadband noise in many practical applications. However, it fails to cope with the uncorrelated narrow-band disturbance picked up by the error sensor, which is independent of the reference signal picked up by the reference sensor. Hence, the alternative switching hybrid ANC has been proposed in the paper to attenuate this kind of uncorrelated narrow-band disturbance effectively. Furthermore, compared with the conventional hybrid ANC algorithms, the proposed algorithm alternatively switches to do updating between the feedforward (FF) and feedback (FB) ANC. The algorithm, thus, saves the computations and achieves a faster convergence speed. The numerical simulations and real-time experiments in the paper validate the effectiveness of the proposed algorithm, which exhibits better convergence and noise reduction performance than other hybrid active control algorithms.