Optimal Selection of the Decomposition Structure Based on GA for Distributed Model Predictive Control Systems

被引：0

作者：

Cai, Xing ^{[1
]}

Xie, Lei ^{[1
]}

Lu, Pengcheng ^{[1
]}

Chen, Junghui ^{[2
]}

机构：

[1] Zhejiang Univ, Inst Cyber Syst & Control, Natl Key Lab Ind Control Technol, Hangzhou 310027, Zhejiang, Peoples R China

[2] Chung Yuan Christian Univ, Dept Chem Engn, Chungli 320, Taiwan

来源：

2014 11TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION (WCICA) | 2014年

关键词：

Input-output grouping decomposition; System decomposition; Genetic algorithm; ALGORITHM;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A novel approach based on Genetic algorithm (GA) is proposed to find out the optimal decomposition structure for distributed model predictive control (DMPC) systems. The decomposition problem of DMPC requires a proper definition of the decomposition index and an efficient algorithm to solve the optimal decomposition optimization problem. In this paper, a new decomposition index representing both the coupling of subsystems and the communication load is defined. Besides, GA is utilized to solve the specific decomposition problem. To generate a new population for the improvement of the DMPC decomposition structure, the GA operators, including coding, selection, mutation and intercross of GA, are proposed to achieve the minimal coupling and the low communication load among subsystems. Finally, a ten-by-ten system is presented to demonstrate the effectiveness of the proposed algorithm.

引用

页码：4560 / 4565

页数：6

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