Control-relevance is a paradigm that interconnects identification with successive model-based control design. Hereby, the current controller, used to conduct identification experiments, is an important factor to success in the design of a new, improved controller. The aim of this paper is to investigate the role of the experimental controller in robust-control-relevant modeling. Such a study is sensible only when unnecessary conservatism is prevented in the construction of perturbed model sets. Hereto, this paper establishes a model uncertainty description that transparently connects to the imposed robust performance criterion. By confronting the developed approach with a next-generation industrial wafer stage, the important role of the experimental controller during modeling for robust control is clarified indeed. It turns out that only after an increase of performance in successive control design iterations, construction of higher order model sets becomes both feasible and significant. As such, in pursuit of performance optimization up to fundamental limits, the experimental controller ensures a gradual extrapolation of the current experimental conditions.
|Title of host publication||Proceedings of the 2010 American Control Conference (ACC 2010), 30 June 30 - 2 July 2010, Baltimore, Maryland, USA|
|Publication status||Published - 2010|