A fuzzy neural network feedback active noise controller

Author

Van Tuan, Huynh ; Nghia, Duong Hoai

Author_Institution

Univ. of Natural Sci., Vietnam Nat. Univ., Ho Chi Minh City

fYear

2008

fDate

17-20 Dec. 2008

Firstpage

1109

Lastpage

1114

Abstract

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.

Keywords

Lyapunov methods; active noise control; compensation; feedback; filtering theory; fuzzy control; fuzzy neural nets; gradient methods; learning systems; least mean squares methods; neurocontrollers; power amplifiers; active noise control system; compensation; discrete Lyapunov function; error gradient descent method; fuzzy neural network feedback active noise controller; fuzzy neural-based filtered-X least-mean-square algorithm; online dynamic learning algorithm; power amplifier; Active noise reduction; Control systems; Convergence; Fuzzy control; Fuzzy neural networks; Fuzzy systems; Heuristic algorithms; Least squares approximation; Neurofeedback; Power amplifiers; Active noise control; convergence; filtered-X least-mean-square algorithm; fuzzy neural network; saturation compensation;

fLanguage

English

Publisher

ieee

Conference_Titel

Control, Automation, Robotics and Vision, 2008. ICARCV 2008. 10th International Conference on

Conference_Location

Hanoi

Print_ISBN

978-1-4244-2286-9

Electronic_ISBN

978-1-4244-2287-6

Type

conf

DOI

10.1109/ICARCV.2008.4795675

Filename

4795675