Discrete-time model reduction of sampled systems using an enhanced multiresolutional dynamic genetic algorithm

研究成果: 雜誌貢獻期刊論文同行評審

4 引文 斯高帕斯(Scopus)

摘要

A framework to automatically generate a reduced-order discrete-time model for the sampled system of a continuous plant preceded by a zero-order hold using an enhanced multiresolutional dynamic genetic algorithms (EMDGA) is proposed in this paper. Chromosomes consisting of the denominator and the numerator parameters of the reduced-order model are coded as a vector with floating point type components and searched by the genetic algorithm. Therefore, a stable optimal reduced-order model satisfying the error range specified can be evolutionarily obtained. Because of the use of the multiresolutional dynamic adaptation algorithm and genetic operators, the convergence rate of the evolution process to search for an optimal reduced-order model can be expedited. Another advantage of this approach is that the reduced discrete-time model evolves based on samples directly taken from the continuous plant, instead of the exact discrete-time model, so that computation time is saved.

原文英語
頁(從 - 到)280-285
頁數6
期刊Proceedings of the IEEE International Conference on Systems, Man and Cybernetics
1
DOIs
出版狀態已發佈 - 2001
對外發佈

ASJC Scopus subject areas

  • 控制與系統工程
  • 硬體和架構

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