Model validation for control and controller validation in a prediction error identification framework - Part I: theory

We propose a model validation procedure that consists of a prediction error identi6cation experiment with a full order model. It delivers a parametric uncertainty ellipsoid and a corresponding set of parameterized transfer functions, which we call prediction error (PE) unceminty set. Such uncertainty set differs from the classical uncertainty descriptions used in robust control analysis and design. We develop a robust control analysis theory for such unceminty sets, which covers two distinct aspects: (1) Controller validation. We present necessary and sufficient conditions for a specific controller to stabilize-or to achieve a given level of performance with-all systems in such PE uncertainty set (2) Model validationfor robust control. We present a measure for the size of such PE uncertainty set that is directly connected to the size of a set controllers that stabilize all systems in the model uncertainty set This allows us to establish that one uncertainty set is better tuned for robust control design than another, leading to control-oriented validation objectives. O 2002 Elsevier Science Ltd. All rights resewed. Keywordx System identification; Identification for robust control; Model validation; Controller validation