Abstract
Within a stochastic noise framework, the validation of a model yields an ellipsoidal parameter uncertainty set, from which a corresponding uncertainty set can be constructed in the space of transfer functions. We display the role of the experimental conditions used for validation on the shape of this validated set, and we connect a measure of the size of this set to the stability margin of a controller designed from the nominal model. This allows one to check stability robustness for the validated model set and to propose guidelines for validation design.
The authors acknowledge the Belgian Programme on Inter-university Poles of Attraction, initiated by the Belgian State, Prime Minister’s Office for Science, Technology and Culture. The scientific responsibility rests with its authors.
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© 1999 Springer-Verlag London Limited
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Gevers, M., Bombois, X., Codrons, B., De Bruyne, F., Scorletti, G. (1999). The role of experimental conditions in model validation for control. In: Garulli, A., Tesi, A. (eds) Robustness in identification and control. Lecture Notes in Control and Information Sciences, vol 245. Springer, London. https://doi.org/10.1007/BFb0109861
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DOI: https://doi.org/10.1007/BFb0109861
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