Low-Delay and Low-Cost Sigma-Delta Adaptive Controller for Active Noise Control

2022 ◽  
Author(s):  
Paulo A. C. Lopes
Keyword(s):  
Noise Control ◽  
Low Cost ◽  
Active Noise Control ◽  
Adaptive Controller ◽  
Sigma Delta ◽  
Low Delay ◽  
Active Noise

scholarly journals A Smart Floating Gate Transistor with Two Control Gates for Active Noise Control

Micromachines ◽  
2019 ◽  
Vol 10 (11) ◽  
pp. 722
Author(s):  
Mao ◽  
Yang ◽  
Ma ◽  
Yan ◽  
Zhang
Keyword(s):  
Large Scale ◽  
Noise Control ◽  
Low Cost ◽  
Active Noise Control ◽  
Complementary Metal Oxide Semiconductor ◽  
Floating Gate ◽  
Oxide Semiconductor ◽  
Cmos Process ◽  
Active Noise ◽  
Floating Gate Transistor

A smart floating gate transistor with two control gates was proposed for active noise control in bioelectrical signal measurement. The device, which is low cost and capable of large-scale integration, was implemented in a standard single-poly complementary metal–oxide–semiconductor (CMOS) process. A model of the device was developed to demonstrate the working principle. Theoretical analysis and simulation results proved the superposition of the two control gates. A series of test experiments were carried out and the results showed that the device was in accordance with the basic electrical characteristics of a floating gate transistor, including the current–voltage (I–V) characteristics and the threshold characteristics observed on the two control gates. Based on the source follower circuit, the experimental results proved that the device can reduce interference by more than 29 dB, which demonstrates the feasibility of the proposed device for active noise control.

Root Locus Analysis of the Adaptation Process in Active Noise Control for Repetitive Impulses

2015 ◽  
Vol 138 (1) ◽  
Author(s):  
Guohua Sun ◽  
Mingfeng Li ◽  
Teik C. Lim
Keyword(s):  
Noise Control ◽  
Active Noise Control ◽  
Adaptive Controller ◽  
Adaptation Process ◽  
Root Locus ◽  
Step Size ◽  
Analysis And Design ◽  
Active Noise ◽  
Graphical Tool ◽  
Fxlms Algorithm

The popular filtered-x least-mean squares (FxLMS) algorithm has been widely adopted in active noise control (ANC) for relatively stationary disturbances. The convergence behavior of the FxLMS algorithm has been well understood in the adaptation process for stationary sinusoidal or stochastic white noises. Its behavior for transient impulses has not received as much attention. This paper employs the root locus theory to develop a graphical tool for the analysis and design of the adaptive ANC system for repetitive impulses. It is found that there is a dominant pole controlling the stability of the adaptation process, in which the maximum step size can be determined. The analysis also observes a transient adaptation behavior in the FxLMS algorithm for repetitive impulses. In this case, the predicted step-size bound decreases as the number of repetitive impulses increases for a general secondary path. Furthermore, the dominant root tuning process is applied by incorporating a digital filter after the output of the adaptive controller, which significantly increases the step-size bound. The accuracy of the analysis was extensively validated by numerical simulation studies by assuming various secondary path models. The simulated results show an excellent agreement with analytical predictions.

Research of Quantum Algorithm for Adaptive Active Noise Control System

2012 ◽  
Vol 457-458 ◽  
pp. 196-201
Author(s):  
Wei Jiang
Keyword(s):  
Control System ◽  
Adaptive Algorithm ◽  
Noise Control ◽  
Active Noise Control ◽  
Quantum Algorithm ◽  
Adaptive Controller ◽  
Lms Algorithm ◽  
Mean Square ◽  
Least Mean Square ◽  
Active Noise

Adaptive active noise control based on least mean square (LMS) algorithm is a linear adaptive filter so that it cannot obtain desired noise reduction. Quantum algorithm is combined with noise control to form quantum adaptive controller. Quantum adaptive algorithm is discussed completely and noise control system is simulated in order to analyze the effects of noise control.

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