A fuzzy neural network feedback active noise controller

This paper presents a fuzzy neural-based filtered-X least-mean-square (LMS) algorithm for active noise control (ANC) system. The saturation of the power amplifier in ANC system is considered. A method for compensating the saturation is proposed. An on line dynamic learning algorithm based on the err...

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Bibliographic Details
Published in:	2008 10th International Conference on Control, Automation, Robotics and Vision pp. 1109 - 1114
Main Authors:	Huynh Van Tuan, Duong Hoai Nghia
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01-12-2008
Subjects:	Active noise control Active noise reduction Control systems Convergence filtered-X least-mean-square algorithm Fuzzy control fuzzy neural network Fuzzy neural networks Fuzzy systems Heuristic algorithms Least squares approximation Neurofeedback Power amplifiers saturation compensation
Online Access:	Get full text
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Summary:	This paper presents a fuzzy neural-based filtered-X least-mean-square (LMS) algorithm for active noise control (ANC) system. The saturation of the power amplifier in ANC system is considered. A method for compensating the saturation is proposed. An on line dynamic learning algorithm based on the error gradient descent method is carried out. The convergence of the algorithm is proven using a discrete Lyapunov function. Simulation results are provided for illustration.
ISBN:	9781424422869 1424422868
DOI:	10.1109/ICARCV.2008.4795675