scholarly journals A Model Predictive Algorithm for Active Control of Nonlinear Noise Processes

2005 ◽  
Vol 12 (3) ◽  
pp. 227-237 ◽  
Author(s):  
Qi-Zhi Zhang ◽  
Woon-Seng Gan ◽  
Ya-li Zhou
Keyword(s):  
Time Delay ◽  
Active Noise Control ◽  
Weight Vector ◽  
Fir Filter ◽  
Secondary Source ◽  
Least Mean Square ◽  
Predictive Algorithm ◽  
Primary Path ◽  
Fxlms Algorithm ◽  
Adaptive Fir

In this paper, an improved nonlinear Active Noise Control (ANC) system is achieved by introducing an appropriate secondary source. For ANC system to be successfully implemented, the nonlinearity of the primary path and time delay of the secondary path must be overcome. A nonlinear Model Predictive Control (MPC) strategy is introduced to deal with the time delay in the secondary path and the nonlinearity in the primary path of the ANC system. An overall online modeling technique is utilized for online secondary path and primary path estimation. The secondary path is estimated using an adaptive FIR filter, and the primary path is estimated using a Neural Network (NN). The two models are connected in parallel with the two paths. In this system, the mutual disturbances between the operation of the nonlinear ANC controller and modeling of the secondary can be greatly reduced. The coefficients of the adaptive FIR filter and weight vector of NN are adjusted online. Computer simulations are carried out to compare the proposed nonlinear MPC method with the nonlinear Filter-x Least Mean Square (FXLMS) algorithm. The results showed that the convergence speed of the proposed nonlinear MPC algorithm is faster than that of nonlinear FXLMS algorithm. For testing the robust performance of the proposed nonlinear ANC system, the sudden changes in the secondary path and primary path of the ANC system are considered. Results indicated that the proposed nonlinear ANC system can rapidly track the sudden changes in the acoustic paths of the nonlinear ANC system, and ensure the adaptive algorithm stable when the nonlinear ANC system is time variable.

scholarly journals Virtual Secondary Path Algorithm for Multichannel Active Control of Vehicle Powertrain Noise

2013 ◽  
Vol 135 (5) ◽  
Author(s):  
Jie Duan ◽  
Mingfeng Li ◽  
Teik C. Lim ◽  
Ming-Ran Lee ◽  
Ming-Te Cheng ◽  
...  
Keyword(s):  
Control System ◽  
Noise Control ◽  
Multiple Input Multiple Output ◽  
Active Noise Control ◽  
Least Mean Square ◽  
Multiple Channel ◽  
Fxlms Algorithm ◽  
Input Multiple Output ◽  
Dependent Property ◽  
Vehicle Powertrain

An enhanced multiple-input multiple-output (MIMO) filtered-x least mean square (FXLMS) algorithm using improved virtual secondary path is proposed as the basis for an active noise control (ANC) system for treating vehicle powertrain noise. This new algorithm is developed to overcome the limitation caused by the frequency-dependent property of the standard FXLMS algorithm and to reduce the variation of convergence speed inherent in multiple-channel cases, in order to improve the overall performance of the control system. In this study, the convergence property of the proposed algorithm is analyzed in the frequency domain in order to yield a better understanding of the physical meaning of the virtual secondary path. In practice, because of the arrangement and sensitivities of the actuators (speakers), transducers (microphones), and physical environment, the magnitude response of the main secondary paths can be very different from each other. This difference will cause difficulty in the overall convergence of the algorithm, which will result in minimal attenuation at some of the channels. The proposed channel equalized (CE) virtual secondary path algorithm is designed to tackle this difficulty by equalizing the mean magnitude level of the main secondary paths and by adjusting other secondary paths correspondingly to keep the coupling effects among the control channels unchanged. The performance of the proposed algorithm is validated by analyzing a two-input two-output active powertrain noise control system.

Comparison Study of Active Noise Cancelation Algorithms for Impulsive Noise

2011 ◽  
Author(s):  
Peng Li ◽  
Xun Yu
Keyword(s):  
Impulsive Noise ◽  
Active Noise Control ◽  
Practical Implementation ◽  
Least Mean Square ◽  
Advantages And Disadvantages ◽  
Residual Noise ◽  
Active Noise ◽  
Fxlms Algorithm ◽  
Important Challenge ◽  
M Estimate

Control of impulsive noise is one important challenge for the practical implementation of active noise control (ANC) systems. The advantages and disadvantages of popular filtered-X least mean square (FXLMS) ANC algorithm and nonlinear filtered-X least mean M-estimate (FXLMM) algorithm are discussed in this paper. A new modified FXLMM algorithm is also proposed to achieve better performance in controlling impulsive noise. Computer simulations are carried out for all the three algorithms and the results are presented and analyzed. The results show that the FXLMM and modified FXLMM algorithms are more robust in suppressing the adverse effect of sudden large amplitude impulses than FXLMS algorithm. In particular, the proposed modified FXLMM algorithm can achieve better stability without sacrificing the performance of residual noise when encountering impulses.

Active Noise Cancellation for a Three-Dimensional Enclosure by Using Multiple-Channel Adaptive Control and H∞ Control

1998 ◽  
Vol 120 (4) ◽  
pp. 958-964 ◽  
Author(s):  
M. R. Bai ◽  
Z. Lin
Keyword(s):  
Digital Signal Processor ◽  
Random Noise ◽  
Active Noise Control ◽  
Three Dimensional ◽  
Internal Field ◽  
Least Mean Square ◽  
Control Structures ◽  
Multiple Channel ◽  
Active Noise ◽  
Fxlms Algorithm

Active noise control (ANC) techniques for a three-dimensional enclosure are compared in terms of two control structures and two control algorithms. The multiple-channel filtered-x least-mean-square (FXLMS) algorithm and the H∞ robust control algorithm are employed for controller synthesis. Both feedforward and feedback control structures are compared. The Youla’s parameterization is employed in the formulation of the multiple-channel feedback FXLMS algorithm. The algorithms are implemented using a floating-point digital signal processor (DSP). Experiments are carried out to validate the ANC approaches for attenuation of the internal field in a rectangular wooden box. Position and number of actuators and sensors are also investigated. A broadband random noise and an engine noise are chosen as the primary noises in the experiments. The experimental results indicate that the feedforward structure yields a broader band of attenuation than the feedback structure. The FXLMS control and H∞, control achieve comparable performance.

scholarly journals Nonlinear Neural System for Active Noise Controller to Reduce Narrowband Noise

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Minh-Canh Huynh ◽  
Cheng-Yuan Chang
Keyword(s):  
Active Noise Control ◽  
Neural System ◽  
Stability And Convergence ◽  
Least Mean Square ◽  
Neural Controller ◽  
Active Noise ◽  
Fxlms Algorithm ◽  
Simulation Results ◽  
The Stability ◽  
Narrowband Noise

Noise in a dynamic system is practically unavoidable. Today, such noise is commonly reduced using an active noise control (ANC) system with the filtered-x least mean square (FXLMS) algorithm. However, the performance of the ANC system with FXLMS algorithm is significantly impaired in nonlinear systems. Therefore, this paper develops an efficient nonlinear adaptive feedback neural controller (NAFNC) to eliminate narrowband noise for both linear and nonlinear ANC systems. The proposed controller is implemented to update its coefficients without prior offline training by neural network. Hence, the proposed method has rapid convergence rate as confirmed by simulation results. The proposed work also analyzes the stability and convergence of the proposed algorithm. Simulation results verify the effectiveness of the proposed method.

Robust least mean square adaptive FIR filter algorithm

2001 ◽  
Vol 148 (5) ◽  
pp. 332 ◽  
Author(s):  
Z. Banjac ◽  
B. Kovačević ◽  
M. Veinović ◽  
M. Milosavljević
Keyword(s):  
Fir Filter ◽  
Mean Square ◽  
Least Mean Square ◽  
Adaptive Fir

DESIGN OF DECOUPLING ACTIVE NOISE CONTROL SYSTEMS

2006 ◽  
Vol 15 (04) ◽  
pp. 521-536
Author(s):  
F. TARINGOO ◽  
J. POSHTAN ◽  
A. NASIRI ◽  
M. H. KAHAE
Keyword(s):  
Transfer Function ◽  
Control Systems ◽  
Noise Control ◽  
Active Noise Control ◽  
Fir Filter ◽  
Simple Method ◽  
Computational Load ◽  
Active Noise ◽  
Fxlms Algorithm ◽  
Decoupled Systems

In this paper a simple method for multi-channel Active Noise Control (ANC) is introduced. The proposed structure is a combination of an adaptive FIR filter, based on the FXLMS algorithm, and the ALIGN algorithm resulting in a decoupled matrix for secondary path transfer function. This structure thus converts a multi-channel ANC system to decoupled systems which results in the reduction in computational load without affecting the convergence behavior of the FXLMS system.

scholarly journals Comparison of Performance and Computational Complexity of Nonlinear Active Noise Control Algorithms

2011 ◽  
Vol 2011 ◽  
pp. 1-9 ◽  
Author(s):  
Mouayad A. Sahib ◽  
Raja Kamil
Keyword(s):  
Computational Complexity ◽  
Noise Control ◽  
Active Noise Control ◽  
Practical Implementation ◽  
Mean Square ◽  
Least Mean Square ◽  
Computational Load ◽  
Active Noise ◽  
Nonlinear Algorithms ◽  
Fxlms Algorithm

Research on nonlinear active noise control (NANC) revolves around the investigation of the sources of nonlinearity as well as the performance and computational load of the nonlinear algorithms. The nonlinear sources could originate from the noise process, primary and secondary propagation paths, and actuators consisting of loudspeaker, microphone or amplifier. Several NANCs including Volterra filtered-x least mean square (VFXLMS), bilinear filtered-x least mean square (BFXLMS), and filtered-s least mean square (FSLMS) have been utilized to overcome these nonlinearities effects. However, the relative performance and computational complexities of these algorithm in comparison to FXLMS algorithm have not been carefully studied. In this paper, systematic comparisons of the FXLMS against the nonlinear algorithms are evaluated in overcoming various nonlinearity sources. The evaluation of the algorithms performance is standardized in terms of the normalized mean square error while the computational complexity is calculated based on the number of multiplications and additions in a single iteration. Computer simulations show that the performance of the FXLMS is more than 80% of the most effective nonlinear algorithm for each type of nonlinearity sources at the fraction of computational load. The simulation results also suggest that it is more advantageous to use FXLMS for practical implementation of NANC.

Hybrid Active Noise Control of a One-Dimensional Acoustic Duct

2001 ◽  
Vol 124 (1) ◽  
pp. 10-18 ◽  
Author(s):  
E. Esmailzadeh ◽  
A. Alasty ◽  
A. R. Ohadi
Keyword(s):  
Noise Control ◽  
Active Noise Control ◽  
Closed Form Solution ◽  
Form Solution ◽  
Least Mean Square ◽  
One Dimensional ◽  
Acoustic Feedback ◽  
Active Noise ◽  
Adaptive Weight ◽  
Fxlms Algorithm

Based on the closed-form solution of a one-dimensional wave equation, the primary, secondary and acoustic feedback paths for the active control of sound in an acoustic duct have been investigated. Accurate models for the condenser microphone and loudspeaker, which include both the electro-mechanical and mechano-acoustical couplings as well as acoustical damping, have been considered. A generalized form of the filtered-x least mean square (FXLMS) algorithm that uses a more general recursive adaptive weight update equation to improve the performance of the FXLMS algorithm has been developed. Computer simulations were carried out to investigate the performance of acoustical feedback and feedback neutralization as well as the effect of boundary conditions on the performance of active noise control (ANC) systems. Comparisons of the simulation results were carried out.

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