A new algorithm for frequency estimation and disturbance cancellation inspired from induction machine theory

The paper presents a new frequency estimation algorithm based on the model of a two-phase induction motor. Averaging theory is used to show that, for a small adaptation gain and positive initial conditions, the frequency estimator is globally stable. Local exponential convergence is obtained near the nominal frequency. Combined with a gradient-based adaptive algorithm for disturbance rejection, the frequency estimator rejects sinusoidal disturbances of unknown frequencies. Averaging theory is used to show global convergence of the combined algorithm. Active noise control experiments validate the results of the analysis, and show that the algorithm successfully rejects disturbances of unknown frequency, as well as with abrupt and slow frequency variations.