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多变量预测控制结构分解的图论方法
Alternative TitleGraph theory method for multivariate predictive control structure decomposition
王洪瑞1,2,3; 邹涛4; 张鑫1,2; 王美聪5; 陆云松1,2
Department工业控制网络与系统研究室
Source Publication控制理论与应用
ISSN1000-8152
2020
Volume37Issue:9Pages:1904-1912
Indexed ByEI ; CSCD
EI Accession number20204309398841
CSCD IDCSCD:6830019
Contribution Rank1
Funding Organization国家自然科学基金项目(61773366) ; 辽宁省自然基金资助计划(2019-KF-03-07) ; 辽宁省博士启动基金(20180540066) ; 工信部工业互联网创新发展工程及智能制造综合标准化与新模式应用项目(时间敏感网络(TSN)与用于工业控制的对象链接与嵌入统一架构(OPC UA)融合关键技术标准研究与试验验证)
Keyword预测控制 图论 计算复杂度 系统分解
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.

Other Abstract

The computational complexity of the model predictive control algorithm is principally determined by the number of variables and the control time domain. While substantial variables in large-scale complex system will result in the problem of a great deal of computation, in particularly increasing computing burden in the optimization solution of constrained predictive control algorithm. In allusion to the problem, this paper employs adjacency matrix, reachability matrix and correlation matrix to sort out the associations among variables in the transfer function model of the system so that the related control variables are divided into the same one subsystem. Then decompose a large-scale system into divers independent subsystems. And a high dimensional optimization problem will be decomposed into several low dimensional sub optimization problems in order that decrease the computational complexity and the calculation. In the end of the paper applies the method to the multivariable constrained double layered structure predictive control algorithm and verified by simulation, which provides a new idea for the multivariable decomposition method.

Language中文
Citation statistics
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/26554
Collection工业控制网络与系统研究室
Corresponding Author邹涛
Affiliation1.中国科学院沈阳自动化研究所
2.中国科学院机器人与智能制造创新研究院
3.中国科学院大学
4.广州大学机械与电气工程学院
5.沈阳化工大学环境与安全工程学院
Recommended Citation
GB/T 7714
王洪瑞,邹涛,张鑫,等. 多变量预测控制结构分解的图论方法[J]. 控制理论与应用,2020,37(9):1904-1912.
APA 王洪瑞,邹涛,张鑫,王美聪,&陆云松.(2020).多变量预测控制结构分解的图论方法.控制理论与应用,37(9),1904-1912.
MLA 王洪瑞,et al."多变量预测控制结构分解的图论方法".控制理论与应用 37.9(2020):1904-1912.
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