Kernel-based identification with frequency domain side-information

Mixed Time/Frequency-Domain Based Robust Identification

A new robust identification framework that incorporates both time and frequency domain data is proposed. ¹his framework avoids situations where a good data fit in one domain leads to poor fitting in the other. Abstract—In this paper we propose a new robust identification framework that combines both frequency and time-domain experimental data. The main result of the paper shows that the problem...

Frequency Domain System Identification with Instrumental Variable based Algorithm

In this paper we discuss how the time domain subspace based identification algorithms can be modified in order to be applicable when the primary measurements are given as samples of the Fourier transform of the input and output signals or alternatively samples of the transfer function. An instrumental variable (IV) based subspace algorithm is presented. We show that this method is consistent if...

Frequency Domain System Identification

Rule-based autotuning based on frequency domain identification

A frequency domain procedure is proposed for the automatic tuning of proportional integral derivative (PID) controllers. The nonparametric open-loop frequency response function is estimated on-line (in closed loop), and simple discriminatory parameters are obtained, which enable appropriate tuning of the controller. For processes with some prior knowledge of the dynamics, the method removes the...

Frequency Domain Maximum Likelihood Identification

The multivariable maximum-likelihood estimate is derived for the case of frequency domain data. The relation with the time domain estimate is commented upon. The algorithm is analyzed with respect to consistency and expressions of the asymptotic variance is presented.