Recent Results on Model Validation

抄録

Model validation is a means of assessing model quality with respect to experimental data. In a robust control context this amounts to determining whether or not a perturbation model is consistent with observed data. This paper offers a survey of recent results on model validation for H_∞ compatible perturbation models.
Several model paradigms and experiment frameworks are considered. The first is a frequency-domain setting for the data. More recent results deal with discrete-time models and time-domain experimental data. The most relevant framework, continuous-time systems and models, with discrete-time sampled data, is dealt with last. Each of the model invalidation tests offered involve tractable convex optimization problems.