Increasing the robustness of a preconditioned filtered-X LMS algorithm

This letter presents a robustification of the preconditioned filtered-X LMS algorithm proposed by Elliott et al. The method optimizes the average performance for probabilistic uncertainty in the secondary path and relaxes the SPR condition for global convergence. It also prevents large amplification in the preconditioning filters due to secondary path zeros on and/or close to the unit circle, which may yield overactuation in practical applications.