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Improved mu-analysis results by using low order uncertainty modelling techniques

Hecker, Simon (2008) Improved mu-analysis results by using low order uncertainty modelling techniques. AIAA Journal of Guidance, Control and Dynamics, 31 (4). DOI: 10.2514/1.33050.

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Abstract

The paper describes some recent enhancements of symbolic factorization techniques for multivariate Laurent polynomial matrices, which are very effective as a preprocessing step for generating linear fractional representations of low order. The symbolic methods are applied to realize a linear fractional representation of full accuracy and probably minimal order for a very complex linear parametric representation of a Research Civil Aircraft Model. The µ-analysis results obtained with the very accurate and low-order linear fractional representation coincide with the robust stability analysis results obtained from a computationally demanding, optimization-based, worst-case search. Furthermore, it is shown that the quality of the µ-analysis results depends on the accuracy and order of the underlying model, i.e. the tightest upper and lower bounds are obtained using the most accurate and least-order linear fractional representation.

Document Type:Article
Title:Improved mu-analysis results by using low order uncertainty modelling techniques
Authors:
AuthorsInstitution or Email of Authors
Hecker, SimonUNSPECIFIED
Date:2008
Journal or Publication Title:AIAA Journal of Guidance, Control and Dynamics
Volume:31
DOI:10.2514/1.33050
Status:Published
Keywords:low-order uncertainty,
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Aeronautics
HGF - Program Themes:Aircraft Research
DLR - Research area:Aeronautics
DLR - Program:L AR - Aircraft Research
DLR - Research theme (Project):L - Systems & Cabin
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Robotics and Mechatronics > System Dynamics and Control (former Control Design Engineering)
Deposited By: Monika Klauer
Deposited On:14 Oct 2008
Last Modified:12 Dec 2013 20:33

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