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Numerical Approximation of Uncertain Nonlinear Systems
Author(s) -
Gaull Andreas,
Kreuzer Edwin
Publication year - 2008
Publication title -
pamm
Language(s) - English
Resource type - Journals
ISSN - 1617-7061
DOI - 10.1002/pamm.200810885
Subject(s) - nonlinear system , markov chain , set (abstract data type) , dynamical systems theory , mathematical optimization , markov process , computer science , mathematics , state (computer science) , process (computing) , algorithm , physics , machine learning , statistics , quantum mechanics , programming language , operating system
We address qualitative characteristics of dynamical systems and their approximation using set–valued numerical methods, where we aim at robust results. In this spirit, model uncertainties are incorporated into the problem formulation as outcomes of an external stochastic process. The systems under consideration are described in terms of finite state Markov chains. An example serves to illustrate the procedure. (© 2008 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)