Non-parametric system norm estimation of multivariable systems
Paul Tacx (ASML)
T.A.E. Oomen (TU Delft - Team Jan-Willem van Wingerden, Eindhoven University of Technology)
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Abstract
Data-driven estimation of system norms is essential for analyzing, verifying, and designing control systems. Existing data-based methods often do not capture the inter-grid and transient behavior of the system, leading to inaccurate and unreliable system norm estimations. This paper presents a unified approach for accurate and reliable estimation of the H2 and H∞ norm with a limited amount of data. The key step is to exploit local parametric models that explicitly incorporate the inter-grid and transient dynamics. The system norm is estimated through the computation of local system norms of the local parametric models within their the local frequency interval. Simulation and experimental results illustrate the effectiveness of the proposed method.
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