Identification of continuous-time errors-in-variables models

Direct Identification of Continuous - Time Errors - in - Variables Models

A novel direct approach for identifying continuous-time linear dynamic errors-in-variables models is presented in this paper. The effects of the noise on the state-variable filter outputs are analyzed. Subsequently, a search-free algorithm to obtain consistent continuous-time parameter estimates in the errors-in-variables framework is derived. The performances of the proposed algorithm are illu...

A cumulant statistics-based method for continuous-time errors-in-variables model identification

The CONTSID toolbox for Matlab: extensions and latest developments

This paper describes the latest developments for the CONtinuous-Time System IDentification (CONTSID) toolbox to be run with Matlab which includes time-domain identification methods for estimating continuous-time models directly from sampled data. The main additions to the new version aim at extending the available methods to handle wider practical situations in order to enhance the application ...

On some continuous-time modeling and estimation problems for control and communication

The scope of the thesis is to estimate the parameters of continuous-time models used within control and communication from sampled data with high accuracy and in a computationally efficient way. In the thesis, continuous-time models of systems controlled in a networked environment, errors-in-variables systems, stochastic closedloop systems, and wireless channels are considered. The parameters o...

Third-order cumulants based methods for continuous-time errors-in-variables model identification

In this paper, the problem of identifying stochastic linear continuous-time systems from noisy input/output data is addressed. The input of the system is assumed to have a skewed probability density function, whereas the noises contaminating the data are assumed to be symmetrically distributed. The third-order cumulants of the input/output data are then (asymptotically) insensitive to the noise...