SISO方法采用改进的改进极点聚类和遗传算法

J. Singh, C. Vishwakarma, K. Chatterjee
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引用次数: 1

摘要

为了降低大型动态系统的阶数,提出了一种将改进的修正极点聚类与遗传算法相结合的方法。通过改进的修正极点聚类技术和遗传算法分别得到降阶分母和分子多项式。该方法为第k阶约简产生了k个约阶系统。从文献中选取了一个数值算例,证明了该混合方法的可行性,并与现有的降阶方法进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SISO method using improved modified pole clustering and genetic algorithm
To reduce the order of the large-scale dynamic systems, a method has been proposed by merging improved modified pole clustering and Genetic Algorithm. Reduced order denominator and numerator polynomial is obtained via improved modified pole clustering technique and Genetic Algorithm respectively. The method produces `k' number of reduced order systems for kth - order reduction. A numerical example has been taken from the literature to show the viability of the proposed mixed method and also compared with existing order reduction methods.
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