Symbolic manipulation techniques for low order LFT-based parametric uncertainty modelling

Abstract

Symbolic techniques are very useful in obtaining low order LFT-representations of linear parametric models. The main role of symbolic manipulations is to find, via suitable pre-processing steps, equivalent representations of rationally dependent parametric matrices, which automatically lead to lower order LFT-representations. In this paper we give an overview of symbolic processing methods and we propose some new techniques and several enhancements of existing methods. All proposed methods are implemented in the latest version of the LFR-toolbox and served to illustrate the strengths of symbolic processing in obtaining low order LFT-representations of two challenging parametric model examples.