This paper presents a filtered-s Lyapunov algorithm for nonlinear active noise control (NANC) using the filter blank implementation based on functional link artificial neural network (FLANN) filter. First, a Lyapunov function of the tracking error is defined, and adaptive FLANN filter coefficients are then adaptive adjusted based Lyapunov stability theory so that the error converges to zero asymptotically. Analysis of theory and simulation results both show that it has fast error convergence and lower stable state error properties. Moreover, its stability is guaranteed by Lyapunov stability theory.
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