The paper deals with an adaptive observer
methodology for estimating the parameters of an unknown
sinusoidal signal from a measurement perturbed by structured
and unstructured uncertainties. The proposed technique makes
it possible to handle measurement signals affected by structured
uncertainties like, for example, bias and drifts which are
typically present in applications. The stability of the estimator
with respect to bounded additive disturbances is addressed
by Input-to-State Stability arguments. The effectiveness of the
proposed technique is shown through numerical simulations
where comparisons with some recently proposed algorithms are
also provided.
