TP tool - A MATLAB toolbox for TP model transformation

Szabolcs Nagy, Zoltán Petres, P. Baranyi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

29 Citations (Scopus)

Abstract

The Tensor Product model transformation is a numerical method that is capable of uniformly transforming LPV (linear parameter-varying) dynamic models into polytopic forms, both in a theoretical and algorithmic context. Using the TP model transformation, different optimization and convexity constraints can be considered, and transformations can be executed without any analytical interactions, within a reasonable amount of time (irrespective of whether the model is given in the form of analytical equations resulting from physical considerations, as an outcome of soft computing based identification techniques such as neural networks or fuzzy logic based methods, or as a result of a blackbox identification). Thus, the transformation replaces the usual analytical and oftentimes complex conversions with a numerically tractable and straightforward series of operations. The TP model transformation generates two kinds of polytopic models. Firstly, it numerically reconstructs the HOSVD (Higher Order Singular Value) based canonical form of LPV models. This is a new and unique polytopic representation. This form extracts the unique structure and various important properties of a given LPV model in the same sense as the HOSVD does for matrices and tensors. Secondly, the TP model transformation generates various convex polytopic forms, upon which LMI (Linear Matrix Inequality) based multi-objective control design techniques can immediately be executed in order to satisfy the given control performance requirements. TP tool is a MATLAB Toolbox that implements the Tensor Product Model Transformation based Control Design framework. It is available at http://tptool.sztaki.hu.

Original languageEnglish
Title of host publication8th International Symposium of Hungarian Researchers on Computational Intelligence and Informatics, CINTI 2007
Pages483-495
Number of pages13
Publication statusPublished - 2007
Event8th International Symposium of Hungarian Researchers on Computational Intelligence and Informatics, CINTI 2007 - Budapest, Hungary
Duration: Nov 15 2007Nov 17 2007

Other

Other8th International Symposium of Hungarian Researchers on Computational Intelligence and Informatics, CINTI 2007
CountryHungary
CityBudapest
Period11/15/0711/17/07

Fingerprint

MATLAB
Tensors
Soft computing
Linear matrix inequalities
Fuzzy logic
Dynamic models
Numerical methods
Neural networks

Keywords

  • HOSVD
  • LMI
  • LPV
  • MATLAB
  • Polytopic
  • TP

ASJC Scopus subject areas

  • Artificial Intelligence
  • Information Systems

Cite this

Nagy, S., Petres, Z., & Baranyi, P. (2007). TP tool - A MATLAB toolbox for TP model transformation. In 8th International Symposium of Hungarian Researchers on Computational Intelligence and Informatics, CINTI 2007 (pp. 483-495)

TP tool - A MATLAB toolbox for TP model transformation. / Nagy, Szabolcs; Petres, Zoltán; Baranyi, P.

8th International Symposium of Hungarian Researchers on Computational Intelligence and Informatics, CINTI 2007. 2007. p. 483-495.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Nagy, S, Petres, Z & Baranyi, P 2007, TP tool - A MATLAB toolbox for TP model transformation. in 8th International Symposium of Hungarian Researchers on Computational Intelligence and Informatics, CINTI 2007. pp. 483-495, 8th International Symposium of Hungarian Researchers on Computational Intelligence and Informatics, CINTI 2007, Budapest, Hungary, 11/15/07.
Nagy S, Petres Z, Baranyi P. TP tool - A MATLAB toolbox for TP model transformation. In 8th International Symposium of Hungarian Researchers on Computational Intelligence and Informatics, CINTI 2007. 2007. p. 483-495
Nagy, Szabolcs ; Petres, Zoltán ; Baranyi, P. / TP tool - A MATLAB toolbox for TP model transformation. 8th International Symposium of Hungarian Researchers on Computational Intelligence and Informatics, CINTI 2007. 2007. pp. 483-495
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