Nonlinear active noise control in a linear duct

The problem of active noise control in a linear duct is examined. Essentially, a nonlinear inverse to a nonminimum phase actuator is proposed. The nonlinear inverse exploits the non-Gaussian nature of some chaotic and stochastic noise sources. The architecture of the controller is derived using Bayesian estimation theory and is shown to be a combination of a linear adaptive network and a radial basis function (RBF) or Volterra series (VS) network. Because of the nonlinear nature of the controller, the filtered-x least means square (LMS) architecture cannot be used. Hence a modified active noise controller is proposed. Simulation results demonstrate the improvements in performance achievable with the combined linear and nonlinear controller