Reduced order model predictive control - an approach based on system decomposition

被引：0

作者：

Hara, Naoyuki ^{[1
]}

Kojima, Akira ^{[1
]}

机构：

[1] Tokyo Metropolitan Univ, Tokyo 1910065, Japan

来源：

PROCEEDINGS OF SICE ANNUAL CONFERENCE, VOLS 1-8 | 2007年

关键词：

model predictive control; constraint; model reduction; eigenvalue problem;

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：

This paper considers a reduced order model predictive control (MPC) method for constrained discrete-time linear systems. By employing a system decomposition technique for discrete-time linear systems, a reduced order MPC law is derived. The MPC law is improved in terms of control performance and feasibility of the associated optimization problem.

引用

页码：2221 / 2224

页数：4

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