Statistical Machine Learning in Model Predictive Control of Nonlinear Processes

Statistical Machine Learning in Model Predictive Control of Nonlinear Processes

Recurrent neural networks (RNNs) have been widely used to model nonlinear dynamic systems using time-series data. While the training error of neural networks can be rendered sufficiently small in many cases, there is a lack of a general framework to guide construction and determine the generalizatio...

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Bibliographic Details
Main Authors: Zhe Wu, David Rincon, Quanquan Gu, Panagiotis D. Christofides
Format: Article
Language:English
Published: MDPI AG 2021-08-01
Series:Mathematics
Subjects:
generalization error
recurrent neural networks
machine learning
model predictive control
nonlinear systems
Online Access:https://www.mdpi.com/2227-7390/9/16/1912

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https://www.mdpi.com/2227-7390/9/16/1912

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