Decrease of the Computational Load of TP Model Transformation

Tensor product (TP) model transformation method was proposed recently as an automated gateway between a class of non-linear models and linear matrix inequality based control design. The core of the TP model transformation is the higher order singular value decomposition of a large sized tensor, whic...

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Bibliographic Details
Published in2006 IEEE International Conference on Mechatronics pp. 655 - 659
Main Authors Petres, Z., Baranyi, P., Hashimoto, H.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2006
Subjects
Automation
Computer industry
Control design
Explosions
Linear matrix inequalities
Load modeling
Singular value decomposition
Tellurium
Tensile stress
Vectors
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Summary:Tensor product (TP) model transformation method was proposed recently as an automated gateway between a class of non-linear models and linear matrix inequality based control design. The core of the TP model transformation is the higher order singular value decomposition of a large sized tensor, which requires high computational power that is usually out of a regular computer capacity in case of higher dimensionality. This disadvantage restricts the applicability of the TP model transformation method to linear parameter varying state-space models with smaller number of state values. The aim of this paper is to propose a modification of the TP model transformation. The proposed version needs considerable less computational effort. The paper also presents a numerical example that shows considerable less computational load is necessary for typical problems
ISBN:9780780397125
0780397126
DOI:10.1109/ICMECH.2006.252603