随机分形搜索在大规模LTI系统降阶中的应用

I. Khanam, G. Parmar
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引用次数: 6

摘要

利用随机分形搜索(SFS)算法对大规模单输入单输出(SISO)线性时不变(LTI)系统进行了降阶。随机分形搜索(SFS)是一种基于分形概念的元算法。SFS利用随机分形中观察到的扩散特性来探索搜索空间。随机规则像;高斯游走用于改变迭代过程以生成随机分形。这里,对于LTI系统的降阶,使用了SFS算法。将原高阶系统和降阶系统的瞬态响应之间的积分平方误差(ISE)作为目标函数,并将其最小化。还比较了低阶和高阶系统的阶跃响应和频率响应以及瞬态响应参数。ISE与文献中其他现有技术的比较研究也以表格形式给出,以显示算法的优越性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of Stochastic Fractal Search in order reduction of large scale LTI systems
Order reduction of large scale single-input single-output (SISO) linear time invariant (LTI) systems using stochastic fractal search (SFS) algorithm has been presented. Stochastic Fractal Search (SFS) is a metahuristic algorithm growth using the concept of fractal. SFS employs the diffusion property observed in random fractals to explore the search space. Stochastic rules like; Gaussian walks are used to change the iteration process to generate random fractals. Here, for order reduction of LTI system, SFS Algorithm is used. Integral square error (ISE) in between the transient responses of original higher order and reduced order system has been taken as an objective function, which has been minimized. The step and frequency responses of both low and high order systems have also been compared along with the transient response's parameters. A comparative study of ISE with the other existing techniques in the literature has also been given in the tabular form to show the superiority of the algorithm.
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