Single-sensor active noise cancellation using recurrent neural network predictors

Generalized Performance of Neural Network Controllers for Feedforward Active Control of Nonlinear Systems

“…NNs in particular are known to possess the property of being 'universal approximators' [9] and are therefore an attractive blackbox method for the modelling and control of unknown or uncertain nonlinear systems. Many different uses of NNs have been studied, including plant/system modelling [4,[10][11][12][13], feedforward controller design [4,10,14], inverse modelling [15], signal prediction and feedback control [16][17][18][19][20], linear filter selection [21], adaptive parameter estimation for linear controllers [20,22], frequencydomain control [23], multichannel controller design [24], and signal classification [25]. The similarity in structure between NNs and linear filters provides good motivation DOI: 10.61782/fa.2023.0050 3599 for their use in both system modelling and feedforward controller design.…”