.png){kind=icon}
返回
Grouped neural network model-predictive control
.png){kind=icon}
PRE
AI
DOI：10.1016/S0967-0661(02)00184-3.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
This work provides experimental demonstration for a previously proposed parallel model structure for general nonlinear model-predictive control (NMPC). The model comprises of a group of sub-models, each providing prediction of one process output at one selected future point in time. The sub-models are mutually independent and therefore can run in parallel. This work uses neural networks (NNs) for each sub-model, and terms the prediction model as a grouped neural network (GNN). NMPC based on the GNN model is referred to as GNNMPC. This work demonstrates implementation of GNNMPC on a nonlinear, multivariable, constrained pilot-scale distillation unit. (C) 2002 Elsevier Science Ltd. All rights reserved.
Keyword:
experimental
nonlinear
model-predictive
constrained
distillation
control
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:
4.6
论文数:
5.7K
被引数:
1.1W
机构
暂无机构信息
引用论文
Non-thermal Plasma-assisted NOx Reduction over Na-Y Zeolites: The Promotional Effect of Acid Sites
PREAI
分享收藏
Grouped-neural network modeling for model predictive control用于模型预测控制的分组神经网络建模.png)
ISA TRANSACTIONS
ISA TRANSACTIONSIF6.5
PREAI
分享收藏
没有更多内容
没有更多内容