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JACIII Vol.10 No.4 pp. 486-493
doi: 10.20965/jaciii.2006.p0486
(2006)

Paper:

Determination of Different Polytopic Models of the Prototypical Aeroelastic Wing Section by TP Model Transformation

Péter Baranyi*, Zoltán Petres*,**, Péter L. Várkonyi*,
Péter Korondi***, and Yeung Yam****

*Computer and Automation Research Institute of the Hungarian Academy of Sciences, H-1111 Budapest, Kende utca 13-17, Hungary

**Institute of Industrial Science, The University of Tokyo

***Budapest University of Technology and Economics, H-1117 Budapest, Goldmann György tér 3, Hungary

****Automation and Computer-Aided Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China

Received:
September 22, 2005
Accepted:
December 28, 2005
Published:
July 20, 2006
Keywords:
non-linear control design, TP model transformation, convex decomposition
Abstract

The Tensor Product (TP) model transformation is a recently proposed technique for transforming given Linear Parameter Varying (LPV) models into polytopic model form, namely, to parameter varying convex combination of Linear Time Invariant (LTI) models. The main advantage of the TP model transformation is that the Linear Matrix Inequality (LMI) based control design frameworks can immediately be applied to the resulting polytopic models to yield controllers with tractable and guaranteed performance. The effectiveness of the LMI design depends on the type of the convex combination in the polytopic model. Therefore, the main objective of this paper is to study how the TP model transformation is capable of determining different types of convex hulls of the LTI models. The study is conducted trough the example of the prototypical aeroelastic wing section.

Cite this article as:
Péter Baranyi, Zoltán Petres, Péter L. Várkonyi,
Péter Korondi, and Yeung Yam, “Determination of Different Polytopic Models of the Prototypical Aeroelastic Wing Section by TP Model Transformation,” J. Adv. Comput. Intell. Intell. Inform., Vol.10, No.4, pp. 486-493, 2006.
Data files:
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