On the use of a priori knowledge in adaptive inverse control

In adaptive inverse control the coefficients of the controller are adaptively adjusted by an algorithm which is controlled by the input and the error signal. Using a priori knowledge about the plant, the controller can be split into a long fixed and a short adaptive filter. The controller can be made more efficient by feeding back the error signal only in a desired frequency range. A modified objective function allows the minimization of the filtered squared error plus the norm of the controller. The technique is demonstrated with an active noise control (ANC) system where it suppresses the sound pressure level by more than 20 dB(A)