Convex hull generation methods for polytopic representations of LPV models

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

19 Citations (Scopus)

Abstract

The paper focuses on the control design of LPV and qLPV models via TS fuzzy model representation and Linear Matrix Inequality (LMI) based design under the Parallel Distributed Compensation control design framework. The related literature reports considerable research on how to manipulate with LMI's to achieve better control performance. This paper shows that this effort is not enough, the optimization of the control performance must include the convex hull manipulation on the TS fuzzy model beside manipulating with the LMIs. The LMI's guaranty the optimal solution for a given convex hull, but the convex hull representation is not invariant. Furthermore, the solutions by LMI's are very sensitive for the convex hull. The paper proposes a systematic concept for various convex hull manipulation method.

Original languageEnglish
Title of host publicationSAMI 2009 - 7th International Symposium on Applied Machine Intelligence and Informatics, Proceedings
Pages69-74
Number of pages6
DOIs
Publication statusPublished - Sep 10 2009
Event7th International Symposium on Applied Machine Intelligence and Informatics, SAMI 2009 - Herl'any, Slovakia
Duration: Jan 30 2009Jan 31 2009

Publication series

NameSAMI 2009 - 7th International Symposium on Applied Machine Intelligence and Informatics, Proceedings

Other

Other7th International Symposium on Applied Machine Intelligence and Informatics, SAMI 2009
CountrySlovakia
CityHerl'any
Period1/30/091/31/09

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ASJC Scopus subject areas

  • Artificial Intelligence
  • Information Systems
  • Electrical and Electronic Engineering

Cite this

Baranyi, P. (2009). Convex hull generation methods for polytopic representations of LPV models. In SAMI 2009 - 7th International Symposium on Applied Machine Intelligence and Informatics, Proceedings (pp. 69-74). [4956611] (SAMI 2009 - 7th International Symposium on Applied Machine Intelligence and Informatics, Proceedings). https://doi.org/10.1109/SAMI.2009.4956611