From differential equations to PDC controller design via numerical transformation

Péter Baranyi, Domonkos Tikk, Yeung Yam, Ron J. Patton

Research output: Contribution to journalArticle

138 Citations (Scopus)

Abstract

This paper proposes a transformation method capable of transforming analytically given differential equations of dynamic models into Takagi-Sugeno fuzzy inference model (TS fuzzy model), whereupon various parallel distributed compensation (PDC) controller design techniques can readily be executed. Joining the transformation method and the PDC techniques leads to a controller design framework. The transformation method is specialized to minimize the number of fuzzy rules in the resulting TS fuzzy model according to a given acceptable transformation error, the PDC design thus results in a computational complexity minimized controller which is highly desired in many cases of real applications. The paper presents examples to show the effectiveness of the proposed transformation.

Original languageEnglish
Pages (from-to)281-297
Number of pages17
JournalComputers in Industry
Volume51
Issue number3
DOIs
Publication statusPublished - Aug 1 2003

Keywords

  • Complexity reduction
  • Higher order singular value decomposition
  • Parallel distributed compensation controller design
  • Takagi-Sugeno fuzzy inference model

ASJC Scopus subject areas

  • Computer Science(all)
  • Engineering(all)

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