Adaptive Observer-based Sinusoid Identification: Structured and Bounded Unstructured Measurement Disturbances

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.