Anastasiia O. Vediakova

TL;DR: To solve the problem of continuous-time online frequency estimation for a sinusoidal signal with a time-varying amplitude, a novel parameterization method is applied yielding linear regression with three unknown constant parameters.

TL;DR: A method to estimate frequencies of a multi-sinusoidal signal in finite time by transforming this nonlinear problem into a linear regression, where unknown parameters depend on signal frequencies.

TL;DR: The new parameterization approach based on applying delay operators to a measurable signal is proposed and the result is the first order linear regression model with one parameter, which depends on the signal frequency.

TL;DR: In this paper, the frequency estimation of a nonstationary sinusoidal signal is studied and a new identification method is proposed to attenuate the noise influence, which does not require measuring or calculating derivatives of the input signal.

TL;DR: This work combines the well-known predictor feedback approach with the state observer and adaptive scheme for feed-forward disturbance rejection based on disturbance observer to create a new output control approach for a class of MIMO systems with the input delay and unknown multisinusoidal disturbance.