Unsupervised Hybrid Models Integrating Deep Autoencoders and Process Controllers’ Models for Enhanced Process Monitoring and Fault Detection
Mohammad Aghaee,
Stephane Krau,
Ibrahim Melih Tamer
et al.
Abstract:This paper introduces a novel hybrid
process monitoring
model that
integrates long short-term memory autoencoders with process controllers’
models. The parameters of the hybrid model are optimized by minimizing
a novel loss function, which combines the mean square error (MSE)
between controlled variables and their reconstructions from the LSTM-AE
model, along with the MSE of manipulated variables and their reconstructions
obtained with the numerically implemented and exactly a priori known
controller equations… Show more
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