Robust identification with mixed parametric/nonparametric models and time/frequency-domain experiments: theory and an application

Parillo et al. (1999) proposed a robust identification framework, based upon generalized interpolation theory, that allows for combining parametric and nonparametric models and frequency and time-domain experimental data. We illustrate the advantages of this framework over conventional control oriented identification techniques by considering the problem of identifying a two-degree of freedom structure used as a testbed for demonstrating damage-mitigation and life extension control concepts. This structure is poorly damped, leading to time and frequency domain responses that exhibit large peaks, thus rendering the identification problem non-trivial