TY - JOUR
AU - Kavranoǧlu, Davut
AB - 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 L2‐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.
TI - Model comparison and simplification
JF - International Journal of Robust and Nonlinear Control
DO - 10.1002/(SICI)1099-1239(199903)9:3<157::AID-RNC398>3.0.CO;2-8
DA - 1999-03-01
UR - https://www.deepdyve.com/lp/wiley/model-comparison-and-simplification-M00ADOjR0h
SP - 157
EP - 181
VL - 9
IS - 3
DP - DeepDyve
ER -