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Model comparison and simplification
Author(s) -
Andersson Lennart,
Rantzer Anders,
Beck Carolyn
Publication year - 1999
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/(sici)1099-1239(199903)9:3<157::aid-rnc398>3.0.co;2-8
Subject(s) - bounded function , quadratic equation , mathematics , singular value , regular polygon , truncation (statistics) , perturbation (astronomy) , truncation error , mathematical optimization , mathematical analysis , eigenvalues and eigenvectors , physics , geometry , statistics , quantum mechanics
In this paper we consider comparison and simplification of dynamical models. These models may contain non‐linearities as well as uncertainty, where both are described using Integral Quadratic Constraints (IQCs). The proposed method includes simplification by truncation and singular perturbation approximation as special cases. The simplification error is defined in terms of the L 2 ‐induced gain. It is shown that each non‐linear or uncertain system component can be assigned a positive value, computable by convex optimization, such that the simplification error is always bounded by the sum of these values corresponding to the simplified components. Copyright © 1999 John Wiley & Sons, Ltd.