Summary
Robustness had become a central issue in system and control theory, focusing the researchers’ attention from the study of a single model to the investigation of a set of models, described by a set of perturbations of a “nominal” model. This set, often indicated as the uncertainty model set, has to be suitably constructed to describe the inherent uncertainty about the system under consideration and to be used for analysis and design purposes. H ∞ identification methods deliver uncertainty model sets in a form suitable to be used by well-established robust design techniques, based on H ∞ or μ optimization methods. The literature on H ∞ identification is now very extensive. Some of the most relevant contributions related to assumption validation, evaluation of bounds on unmodeled dynamics, convergence analysis, and optimality properties of different algorithms are here surveyed from a deterministic point of view.
This research was supported in part by funds of Ministero dell’niversità e della Ricerca Scientifica e Tecnologica under the Project “Robustness and optimization techniques for control of uncertain systems”.
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Milanese, M., Taragna, M. (2006). Set Membership Identification: The H ∞ Case. In: Menini, L., Zaccarian, L., Abdallah, C.T. (eds) Current Trends in Nonlinear Systems and Control. Systems and Control: Foundations & Applications. Birkhäuser Boston. https://doi.org/10.1007/0-8176-4470-9_3
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