scholarly journals Recursive Least-Squares Lattice Algorithm Combined With Secondary-Path Innovation and Lattice-Order Decision Algorithms for Active Noise Control

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 15952-15962
Author(s):  
Dong Woo Kim ◽  
Poogyeon Park
Keyword(s):  
Least Squares ◽  
Noise Control ◽  
Active Noise Control ◽  
Recursive Least Squares ◽  
Lattice Order ◽  
Active Noise ◽  
Lattice Algorithm ◽  
Decision Algorithms

Application of a Least Squares Lattice Algorithm to Active Noise Control for an Automobile

1997 ◽  
Vol 119 (2) ◽  
pp. 318-320 ◽  
Author(s):  
Hisashi Sano ◽  
Shuichi Adachi ◽  
Hideki Kasuya
Keyword(s):  
Least Squares ◽  
Noise Control ◽  
Active Noise Control ◽  
Broadband Noise ◽  
Lms Algorithm ◽  
Least Mean Square ◽  
The Road ◽  
Active Noise ◽  
Alternative Approach ◽  
Lattice Algorithm

The purpose of this paper is to propose an alternative approach to active noise control (ANC) using the least squares lattice (LSL) algorithm. Typically, in ANC applications, the least-mean-square (LMS) algorithm has been used because of its simplicity. However, the LMS algorithm has the disadvantage of slow convergence speed in the case of broadband noise, such as the road noise present in the passenger compartment of automobiles traveling on rough road surfaces. In order to solve this problem, the LSL algorithm for ANC is considered. By computer simulation using actual car data, the LSL algorithm proves to be more effective than the LMS one.

scholarly journals Design of Self-Tuning Minimum Effort Active Noise Control with Feedback Inclusion Architecture

2009 ◽  
Vol 28 (3) ◽  
pp. 205-215 ◽  
Author(s):  
R. K. Raja Ahmad ◽  
M. O. Tokhi
Keyword(s):  
Noise Control ◽  
Transfer Functions ◽  
Controller Design ◽  
Active Noise Control ◽  
The Self ◽  
Recursive Least Squares ◽  
Single Input Single Output ◽  
Single Output ◽  
Active Noise ◽  
Self Tuning

This paper presents the development of a self-tuning controller design of minimum effort active noise control (ANC) for feedforward single-input single-output (SISO) architecture which includes the feedback acoustic path in the controller formulation. The controller design law is derived for suitable self-tuning implementation and the self-tuning controller is evaluated in a realistically constructed ANC simulation environment. The self-tuning controller design involves a two-stage identification process where the controller is replaced by a switch. This switch is closed and opened in sequence generating two transfer functions which are then used in constructing the controller specified by a minimum effort control law. The implementation requires an estimate of the secondary path transfer function which can be identified either online or offline. The controller design and implementation are evaluated in terms of the level of cancellation at the observer through simulation studies for various values of modified effort weighting parameter in the range 0 ≤ γ ≤ 1. It was found that the optimal controller designed using this technique which is constrained only by the accuracy of the two models identified using recursive least squares algorithm, yields good cancellation level.

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