.png){kind=icon}
返回
Designing a robust minimum variance controller using discrete slide mode controller approach
.png){kind=icon}
PRE
AI
DOI：10.1016/j.isatra.2012.10.004.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Designing minimum variance controllers (MVC) for nonlinear systems is confronted with many difficulties. The methods able to identify MIMO nonlinear systems are scarce. Harsh control signals produced by MVC are among other disadvantages of this controller. Besides, MVC is not a robust controller. In this article, the Vector ARX (VARX) model is used for simultaneously modeling the system and disturbance in order to tackle these disadvantages. For ensuring the robustness of the control loop, the discrete slide mode controller design approach is used in designing MVC and generalized MVC (GMVC). The proposed method for controller design is tested on a nonlinear experimental Four-Tank benchmark process and is compared with nonlinear MVCs designed by neural networks. In spite of the simplicity of designing GMVCs for the VARX models with uncertainty, the results show that the proposed method is accurate and implementable. (C) 2012 ISA. Published by Elsevier Ltd. All rights reserved.
Keyword:
Generalized minimum variance controller
Robust minimum variance controller
VARX model
Discrete slide mode controller
Four-tank benchmark system
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
6.5
论文数:
6.0K
被引数:
2.0W
机构
暂无机构信息
引用论文
The role of vector autoregressive modeling in predictor-based subspace identification.png)
AUTOMATICA
AUTOMATICAIF5.9
PREAI
分享收藏Elliptic Eigenvalue Problems with Large Drift and Applications to Nonlinear Propagation Phenomena
OAAI
OAAI分享收藏
查看更多内容