Experimental Validation of Iterative Learning Control for DC/DC Power Converters

被引：3

作者：

Li, Bingqiang ^{[1
]}

Riaz, Saleem ^{[1
]}

Zhao, Yiyun ^{[1
]}

机构：

[1] Northwestern Polytech Univ, Sch Automat, Xian 710072, Peoples R China

来源：

ENERGIES | 2023年 / 16卷 / 18期

关键词：

DC/DC converters; iterative learning control (ILC); traditional PI control; robust control;

D O I：

10.3390/en16186555

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

In order to solve the problem that the parameters of traditional proportional-integral (PI) control are not easy to adjust, an iterative learning control (ILC) technique for a DC/DC power converter is proposed in this paper. Firstly, we have developed a system which is composed of two different states of DC/DC converter in order to obtain its equivalent linear time-varying system, and then the open-loop PD-type ILC law has been used to control it. Secondly, an experimental setup is arranged to verify and compare the simulated results. The experimental results show that, as compared with the traditional PI control, the proposed strategy is easy to implement and optimal with regard to debugging parameters, and it can achieve zero steady-state tracking errors without overshooting. Finally, the experimental results have also proven that our proposed scheme of iterative learning control for a DC/DC power converter is robust as compared to traditional PI control.

引用

页数：16

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