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 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.