Black-box Modeling with Uncertain Parameters from Measurement Data with Unknown, but Bounded Errors

摘要

In literature, identification of models with uncertain parameters is restricted to parameter identification. This paper presents a method for system identification with unknown, but bounded measurement errors for linear, time-invariant systems. For each system output, the method determines a model order in a first step, and estimates the uncertain parameters in a second step, both from interval measurement data due to the unknown, but bounded errors. It results in a discrete-time model description with interval parameters. The method is demonstrated and discussed using simulated data as well as measurements.