用不同随机分布函数的随机多参数散度优化方法设计分数阶系统的最优分数阶PID控制器

Abdullah Ateş, Baris Baykant Alagöz, Y. Q. Chen, C. Yeroğlu, S. Hosseinnia
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引用次数: 5

摘要

本文利用几种随机分布函数对随机多参数散度优化方法进行了改进,以显示不同随机分布函数对优化性能的影响。SMDO是随机漫步类中的一种参数智能随机搜索算法。SMDO方法的一个突出特点是使用标准均匀分布的随机数,同时对解点的参数进行前后发散,从而得到最优解。SMDO方法得益于随机前后发散的成功。本文研究了四种随机分布函数对控制器调优问题SMDO算法性能的影响。这些分布是卡方分布(CSD)、瑞利分布(RD)、对数正态分布(LND)和均匀随机分布(UD)。为了说明这些随机分布函数的影响,将SMDO应用于分数阶PID (FOPID)控制器的分数阶模型(FOM)整定问题,并对不同分布函数下的结果进行了验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimal Fractional Order PID Controller Design for Fractional Order Systems by Stochastic Multi Parameter Divergence Optimization Method with Different Random Distribution Functions
This paper modifies Stochastic Multi Parameter Divergence Optimization Method (SMDO) by using some types of random distribution functions in order to show effects of different random distribution functions on optimization performance. SMDO is a parameter wise random search algorithm in random walk class. A prominent feature of SMDO method lies in using random number with standard uniform distribution while diverging a parameter of solution point in backward and forward directions to reach an optimal solution. SMDO method benefits from the success of random backward and forward divergences. This study investigates effects of four types of random distribution functions on performance of SMDO algorithm for controller tuning problem. These distributions are Chi-Square Distribution (CSD), Rayleigh Distribution (RD), Log Normal Distribution (LND) and Uniform random (UD) distribution. To illustrate effects of these random distribution functions, SMDO is employed to fractional order PID (FOPID) controller tuning problems for fractional order model (FOM) and results obtained for different distribution functions are demonstrated.
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