Application of Kalman and RLS adaptive algorithms to non-linear loudspeaker controller parameter estimation: a case study

The loudspeaker is a nonlinear transducer that produces harmonic distortion and nonlinear controllers, requiring parameters well tuned to the loudspeaker, are used to reduce it. Unfortunately loudspeaker parameters are not well known and vary during normal operation. Based on a simplified nonlinear model of the loudspeaker, and a modification to the adaptive filters, nonlinear systems for the estimation of parameters for the mechanical part and for the electrical part of the loudspeaker were developed. The parameters estimated are directly usable by the controllers, not requiring additional conversion calculations. The Kalman and RLS adaptive algorithms where applied to this systems and simulation results show that they converge, although the electrical part estimation system was about 15 times slower than the mechanical.