4.7 Article

Centralized PI controller design method for MIMO processes based on frequency response approximation

期刊

ISA TRANSACTIONS
卷 110, 期 -, 页码 117-128

出版社

ELSEVIER SCIENCE INC
DOI: 10.1016/j.isatra.2020.10.041

关键词

Multivariable process; Non-square system; High-dimensional MIMO process; PI controller; Centralized control

向作者/读者索取更多资源

A simple frequency domain method is proposed for the design of controllers for multi-input multi-output (MIMO) processes. By evaluating the process transfer function matrix at a low frequency point, the calculation for inverse of the matrix is simplified. Centralized PI controllers are designed using a model matching technique and provide acceptable performances for different types of processes, including high-dimensional processes.
A simple method of controller design for multi-input multi-output (MIMO) processes have been proposed in frequency domain. The intensive calculation for the inverse of the process transfer function matrix is simplified to a great extent by evaluating the process transfer function matrix at a low frequency point. The desired closed loop transfer functions are derived for the process using a single tuning parameter for each diagonal element of the process transfer function matrix which represents the desired closed loop time constant. Centralized PI controllers are then designed using a model matching technique by evaluating the transfer functions at a low frequency point. The PI controllers provide acceptable performances for lag dominated as well as time-delay dominated processes and is also applicable to high-dimensional processes. The proposed method is extended for the non-square MIMO processes using two approaches one of which squares up the process transfer function matrix to apply the proposed technique while the other is based on pseudo-inverse evaluation of the process transfer function matrix at a low frequency point. (C) 2020 ISA. Published by Elsevier Ltd. All rights reserved.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据