Adaptive active noise feedforward compensation for exhaust ducts using a FIR Youla parametrization. (1st May 2022)

• Record Type: Journal Article
• Authors: Li, Feng; Wu, Zhizheng; Qian, Fanfan; Yue, Tengfei; Xu, Tingyue
• Is Part Of: Mechanical systems and signal processing. Volume 170(2022)
• Publication Date: 2022-05-01
• Subjects: Active noise control -- Feedforward control -- Youla parameterized -- Adaptive -- Acoustic feedback; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2022.108803
• Languages: English
• ISSNs: 0888-3270

Abstract

Highlights : An adaptive feedforward ANC approach is proposed within Youla parameterized control scheme. Both broad-band and narrow-band noise can be effectively attenuated. The stabilization of the acoustic feedback loop is always satisfied. The delay constraint between the secondary path and the primary path is relieved. Abstract: The adaptive feedforward control strategy can effectively attenuate the low-frequency broad-band noise with unknown and variable characteristics. However, most feedforward active noise control systems have the internal acoustic feedback coupling between the secondary noise source and the measurement of the image of the reference noise, which may lead to instability of the system. In addition, there are potential fields of applications in which the broad-band noise source may be mixed with the narrow-band noise components and the delay of the secondary path may be larger than the delay of the primary path. In order to deal with these limitations, in this paper an adaptive Youla( Q ) parameterized feedforward active noise control system is introduced. Firstly, a central controller is designed to stabilize the internal acoustic feedback loop. Then the central controller will be augmented into a Youla( Q ) parameterized FIR-type adaptive controller with the recursive least squares (RLS) adaptive algorithm, and the Q parameter can be adjusted online to the desired value to attenuate the unknown and variable noise. Finally, the proposed adaptive Youla( Q ) parameterized feedforward active noise control approach is successfully applied to the noise attenuation of a "U"-shaped industrial exhaust duct.