An Adaptive Neuro Fuzzy Network for Nonlinear Active Noise Control Systems

This paper presents an Adaptive Neuro Fuzzy Network (ANFN) for enhancing the performance of nonlinear feedforward active noise control systems. The proposed controller is a combination of the fuzzy logic technique and adaptive neural network. The Filtered-X Least Mean Square (FXLMS) algorithm is use...

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Bibliographic Details
Main Authors: Tin, Nguyen Thi Trung, Na, Jing, Le Thai, Nguyen, Huang, Yingbo, Li, Gengen
Format: Conference Proceeding
Language:English
Subjects:
Adaptive Neuro-Fuzzy Network (ANFN)
Adaptive systems
Control systems
filtered-x least-mean-square (FXLMS) algorithm
Fuzzy neural networks
Neural networks
Noise
Nonlinear active noise control (NLANC)
Nonlinear filters
nonlinear path
Simulation
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Description
Summary:This paper presents an Adaptive Neuro Fuzzy Network (ANFN) for enhancing the performance of nonlinear feedforward active noise control systems. The proposed controller is a combination of the fuzzy logic technique and adaptive neural network. The Filtered-X Least Mean Square (FXLMS) algorithm is used to update the weights of the nonlinear ANFN controller. The convergence of the proposed control system is also proven by using a discrete Lyapunov function, and simulation results are given to demonstrate the effectiveness of the proposed method.
ISSN:1934-1768
DOI:10.23919/CCC63176.2024.10662675