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Active Noise Control Using a Fuzzy Inference System Without Secondary Path Modelling

100%

Kurczyk S. , Pawelczyk M.

2014

tom Vol. 39, No. 2

243--248

For many adaptive noise control systems the Filtered-Reference LMS, known as the FXLMS algorithm is used to update parameters of the control filter. Appropriate adjustment of the step size is then important to guarantee convergence of the algorithm, obtain small excess mean square error, and react with required rate to variation of plant properties or noise nonstationarity. There are several recipes presented in the literature, theoretically derived or of heuristic origin. This paper focuses on a modification of the FXLMS algorithm, were convergence is guaranteed by changing sign of the algorithm steps size, instead of using a model of the secondary path. A Takagi-Sugeno-Kang fuzzy inference system is proposed to evaluate both the sign and the magnitude of the step size. Simulation experiments are presented to validate the algorithm and compare it to the classical FXLMS algorithm in terms of convergence and noise reduction.

Active Noise Control Using a Fuzzy Inference System Without Secondary Path Modelling

86%

Kurczyk S. , Pawelczyk M.

Generation of effect of virtual undirectional source of sound using adaptive techniques

72%

Bismor D.

Archives of Control Sciences

2003

tom Vol. 13, no. 2

215-230

One of the main differences between standard industrial automation plants and acoustic plants is the presense of acoustic feedback between the contol value ("active" loudspeaker output) and measured disturbance value (reference microphone) [5]. There are reference sensor or feedback neutralization. This paper presents the author's experience with another approach to the problem, namely virtual unidirectional source of sound [13].