On Tracking Properties of Real-Valued Generalized Adaptive Notch Filters

Generalized adaptive notch filters (GANFs) are used for identification/tracking of quasi-periodically varying dynamic systems and can be considered an extension, to the system case, of classical adaptive notch filters. The paper presents results of local performance analysis of a real-valued GANF algorithm, i.e., algorithm designed to track parameters of a real-valued system. This is an extension of the previous work which focused on complex-valued systems. Tracking properties of the algorithm are studied analytically using an approximating linear filter technique and an averaging approach. Even though restricted to a single frequency case, the presented analysis provides interesting insights into the tracking mechanisms of GANF and allows one to formulate some useful rules of thumb for choosing design parameters