Self-learning active noise control

Abstract

An important step for active noise control ͑ANC͒ systems to be practical is to develop model independent ANC ͑MIANC͒ systems that tolerate parameter variations in sound fields. Reliabilities and stabilities of many MIANC systems depend on results of online system identifications. Parameter errors due to system identifications may threaten closed-loop stabilities of MIANC systems. A self-learning active noise control ͑SLANC͒ system is proposed in this study to stabilize and optimize an ANC system in case identified parameters are unreliable. The proposed system uses an objective function to check closed-loop stability. If partial or full value of the objective function exceeds a conservatively preset threshold, a stability threat is detected and the SLANC system will stabilize and optimize the controller without using parameters of sound fields. If the reference signal is available, the SLANC system can be combined with a feedforward controller to generate both destructive interference and active damping in sound fields. The self-learning method is simple and stable for many feedback ANC systems to deal with a worst case discussed in this study.

Recent advances on active noise control: open issues and innovative applications

“…Detailed online secondary-path modeling algorithms and associated problems will be presented in Section III. Moreover, ANC systems that require no secondary-path models [46][47][48][49][50][51][52][53][54][55][56][57][58][59][60][61][62][63][64][65] will also be introduced in Section III.…”

“…Other ANC techniques that do not require the secon-dary-path model include methods based on the strict positive real (SPR) property of the FXLMS algorithm [62,63], adaptive genetic algorithm [64], and self-learning [65]. Among these algorithms, the SPR-based method is the most attractive owing to its simple implementation and good performance.…”

Improving the Sound Absorption Properties of Flexible Polyurethane (PU) Foam using Nanofibers and Nanoparticles

“…Meanwhile, additive manufacturing technology has advantages in designing open-cell structures [13,14]. In recent years, sound control has been of interest to researchers, especially at low frequencies where important innovations have occurred in sound control technology such as active noise cancellation systems [15,16] and sound absorbing structures [17,18], which have gained popularity in recent decades. One of the important sound control technologies is modifying materials using nanotechnology, which has proved effective over wide bandwidths for sound control.…”

Effects of equivalent series resistance on the noise mitigation performance of piezoelectric shunt damping

“…Scientific studies have suggested that many psychological stresses, chronic hearing losses and cardiovascular illnesses among the city-dwellers can be linked to excessive exposure to environmental noise [1,2]. To create a more livable city, innovations on noise control technologies, such as active noise cancellation systems [3,4] and sound absorbing structures [5,6], have undergone substantial advancement since the last decade.…”