.png){kind=icon}
返回
Nonlinear offset-free model predictive control
.png){kind=icon}
PRE
AI
DOI：10.1016/j.automatica.2012.06.038.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
This paper addresses offset-free reference tracking of asymptotically constant reference signals using Model Predictive Control. Existing results for linear models are extended to general nonlinear models. The core of the proposed method employs a disturbance model and an observer to estimate its state. Typical disturbance models are shown and the implications of using them are discussed. Conditions are given for which this setup eliminates the tracking error asymptotically. Basically, we prove that error free output estimation and error free nominal tracking imply offset-free Model Predictive Control. (C) 2012 Elsevier Ltd. All rights reserved.
Keyword:
Control of constrained systems
Output feedback control
Disturbance rejection
Tracking
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:
5.9
论文数:
1.2W
被引数:
5.2W
机构
引用论文
分享收藏
Robust output feedback model predictive control using off-line linear matrix inequalities基于离线线性矩阵不等式的鲁棒输出反馈模型预测控制
PREAI
分享收藏Characterisation of a complementary DNA encoding a novel plant enzyme with sucrolytic activity.png)
FEBS Letters
OAAI
FEBS LettersIF0
OAAI分享收藏
查看更多内容