AN ACTIVE NOISE CONTROLLER USING TYPE-2 FUZZY NEURAL NETWORK
Abstract
SUMMARY
This paper presents a feedback active noise control system using type-2 fuzzy neural network. The new features of the proposed system are: firstly we introduce a saturation compensator for the actuator and secondly we use a type 2 fuzzy neural network to estimate the nonlinearity of the secondary path transfer function. Online dynamic back-propagation learning algorithm based on the error gradient descent method is proposed. The condition of convergence of the proposed algorithm is derived using a discrete Lyapunov function. Simulation results show that the proposed method is effective.
This paper presents a feedback active noise control system using type-2 fuzzy neural network. The new features of the proposed system are: firstly we introduce a saturation compensator for the actuator and secondly we use a type 2 fuzzy neural network to estimate the nonlinearity of the secondary path transfer function. Online dynamic back-propagation learning algorithm based on the error gradient descent method is proposed. The condition of convergence of the proposed algorithm is derived using a discrete Lyapunov function. Simulation results show that the proposed method is effective.
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PDF (Tiếng Việt)DOI: https://doi.org/10.15625/0866-708X/48/2/1121 Display counter: Abstract : 42 views. PDF (Tiếng Việt) : 29 views.
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Published by Vietnam Academy of Science and Technology