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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(More)
This paper deals with a novel robust estimation methodology yielding the amplitudes, frequencies and phases of the components of a biased multi-sinusoidal signal in presence of a bounded disturbance on the measurement. The proposed method is based on a suitable adaptive observer in which the parameters’ adaptation law is equipped with an excitationbased(More)
This paper deals with a novel adaptive observer-based technique for estimating the amplitude, frequency, and phase of a single sinusoidal signal from a measurement affected by structured and unstructured disturbances. The structured disturbances are modeled as a time-polynomial so as to represent bias and drift phenomena typically present in applications,(More)
In this paper, a parallel pre-filtering scheme is presented to address the problem of estimating the parameters of a sinusoidal signal from biased and noisy measurements. Extending some recent result on pre-filtering-based frequency estimators, a parallel pre-filtering scheme is proposed to deal with the unknown offset and bounded measurement perturbations,(More)
OBJECTIVE To investigate the effect of baicalein and quercetin on the enzymatic resistance of dentin matrix collagen. METHODS Baicalein, quercetin and proanthocyanidin were dissolved in 20% dimethyl sulfoxide (DMSO) ethanol and prepared into pretreatment agents with a concentration of 50 g/L. Demineralized dentin specimens were prepared and immersed in(More)
A novel finite-time convergent estimation technique is proposed for identifying the amplitude, frequency and phase of a biased sinusoidal signal. Resorting to Volterra integral operators with suitably designed kernels, the measured signal is processed yielding a set of auxiliary signals in which the influence of the unknown initial conditions is removed. A(More)