Nonlinear active noise control using Lyapunov theory and RBF network

Author

Phooi, Seng Kah ; Zhihong, Man ; Wu, H.R.

Author_Institution

Sch. of Eng., Tasmania Univ., Hobart, Tas., Australia

Volume

2

fYear

2000

fDate

2000

Firstpage

916

Abstract

A new approach to design an efficient algorithm for the ANC system is proposed. The transversal filter-based controllers (FIR and IIR) are first considered. A Lyapunov function of the error is defined and filter coefficients are then adaptively adjusted based on Lyapunov stability theory so that the error converges to zero asymptotically. The design is independent of the statistical properties of signals and its computational complexity is comparable to FXLMS. It has fast error convergence properties and the stability is guaranteed by Lyapunov stability theory. This scheme can be further extended to an efficient nonlinear ANC using an RBF network for excellent performance. Simulation examples are demonstrated to show the degree of noise cancellation this scheme can achieve

Keywords

Lyapunov methods; active noise control; adaptive filters; computational complexity; neurocontrollers; nonlinear control systems; radial basis function networks; stability; ANC system; Lyapunov function; Lyapunov stability theory; RBF network; computational complexity; error; error convergence; noise cancellation; nonlinear active noise control; radial basis function network; simulation; transversal filter-based controllers; Active noise reduction; Adaptive filters; Algorithm design and analysis; Computational complexity; Filtering theory; Finite impulse response filter; IIR filters; Lyapunov method; Signal design; Transversal filters;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks for Signal Processing X, 2000. Proceedings of the 2000 IEEE Signal Processing Society Workshop

Conference_Location

Sydney, NSW

ISSN

1089-3555

Print_ISBN

0-7803-6278-0

Type

conf

DOI

10.1109/NNSP.2000.890172

Filename

890172