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Graph theory method for multivariate predictive control structure decomposition
Authors
张鑫
王洪瑞
+3 more
王美聪
邹涛
陆云松
Publication date
1 January 2020
Publisher
Abstract
预测控制算法的计算复杂度主要由变量个数和控制时域决定,而大型复杂系统中变量个数较多将导致计算量大的问题,尤其在有约束预测控制的优化求解中增加较重的计算负担.本文针对此问题利用邻接矩阵、可达矩阵和关联矩阵梳理系统传递函数模型中变量之间的关联,将有关联的控制变量划分为一个子系统,进而将一个大系统分解成若干独立子系统,即可将一个高维度的优化求解问题分解成多个维度较低的子优化问题,降低计算复杂度以达到减少计算量的目的.最后将其应用在多变量有约束的双层结构预测控制算法中,通过仿真进行验证.</p
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Last time updated on 16/09/2020