This talk explores the advantages of the frequency domain for the identification of time-varying systems. First, we will discuss how valuable and sensible information can be extracted from these systems by using well-designed periodic excitation signals and, surprisingly, by interpreting the measurement results in the frequency domain. The spectral response allows for a visual detection and classification of time variation, nonlinear distortion and noise. Also, a non-parametric estimate of the time-varying transfer function is extracted. Then, the estimation of parametric models is discussed. Discrete- and continuous-time linear time-varying systems are identified by cleverly switching between the time and the frequency domain. A consistent estimator is defined to take input and output noise into account. Finally, opportunities are discussed to use kernel based regression to alleviate the difficult task of model structure selection. These concepts and techniques will be illustrated on simulation and measurement examples.
Original languageEnglish
Publication statusUnpublished - Nov 2019
Event3rd IFAC Workshop on Linear Parameter-Varying Systems, - Eindhoven University of Technology , Eindhoven, Netherlands
Duration: 4 Nov 20196 Nov 2019


Conference3rd IFAC Workshop on Linear Parameter-Varying Systems,
Abbreviated titleLPVS 2019
Internet address

ID: 48955808