Improved large signal performance of linear controlled input-series and output-parallel dc-dc converter using genetic algorithm optimization

S. M. Khazraei, A. Jasour, A. Rahmati, A. Abrishamifar
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引用次数: 3

Abstract

An input-series and output-parallel (ISOP) connected converter is one of the recently developed multi- module converters. The suitable control scheme for this type of converter necessitates equal voltage sharing for input- series connected modules and output current sharing for the output-parallel connected modules for all operating conditions even with existence of dissimilarity in devices and components used in each module. Such control scheme consisting of several controllers can be implemented using analog controllers. This paper presents a genetic algorithm (GA) which optimizes the parameters of analog controllers for each control loop in the control scheme of an ISOP connected converter. Using GA eliminates the need for tedious and time consuming small signal analysis of multi- module converters. Moreover, because GA chooses the best value for each parameters in different control loops simultaneously it can best consider the interaction among all loops and results in better large signal performance especially in the case of large variations in the parameters or considerable difference among modules of converter.
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利用遗传算法优化改进了线性控制输入串联和输出并联dc-dc变换器的大信号性能
输入串联输出并联(ISOP)连接变换器是近年来发展起来的一种多模块变换器。对于这种类型的变换器,适当的控制方案要求在所有工作条件下,即使在每个模块中使用的器件和元件不相同的情况下,输入串联模块的电压分担相等,输出并联模块的输出电流分担相等。这种由多个控制器组成的控制方案可以使用模拟控制器来实现。本文提出了一种遗传算法,用于优化ISOP连接变换器控制方案中各控制回路的模拟控制器参数。采用遗传算法消除了对多模块变换器进行繁琐、耗时的小信号分析的需要。此外,由于遗传算法同时选取不同控制回路中各参数的最优值,因此可以最好地考虑各回路之间的相互作用,特别是在变换器参数变化较大或模块间差异较大的情况下,具有更好的大信号性能。
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