Model reduction of discrete interval systems using genetic algorithms

研究成果: 雜誌貢獻文章同行評審

摘要

In this paper, an evolutionary approach is proposed to derive a reduced-order model for discretetime interval systems based on resemblance of discrete sequence energy between the original and reduced systems. With the use of the recursive algebraic algorithm and interval arithmetic manipulations, the problem to identify boundaries of the uncertain coefficients of the reduced-order model can be formulated as an optimization problem, which is subsequently solved by a proposed genetic algorithm. To demonstrate the effectiveness of the proposed approach, system performance of the reduced-order discrete interval model is validated based on time responses in comparison to existing approaches. Because of the time-consuming process that genetic algorithms generally exhibit, particularly the problem nature which demands heavy calculation of the fitness function, a parallel computation scheme is also presented to accelerate the evolution process to derive the reduced-order model.

原文英語
頁(從 - 到)2073-2080
頁數8
期刊WSEAS Transactions on Systems
4
發行號11
出版狀態已發佈 - 2005 十一月 1

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications

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