Search Results - "Journal of process control" :: K.UTB vyhledávací portál

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A novel dynamic PCA algorithm for dynamic data modeling and process monitoring

by Dong, Yining, Qin, S. Joe
Published in Journal of process control (01.07.2018)

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An identification algorithm of generalized time-varying systems based on the Taylor series expansion and applied to a pH process

by Ji, Yan, Liu, Jian, Liu, Haibo
Published in Journal of process control (01.08.2023)

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Perspectives on nonstationary process monitoring in the era of industrial artificial intelligence

by Zhao, Chunhui
Published in Journal of process control (01.08.2022)

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Repetitive process based indirect-type iterative learning control for batch processes with model uncertainty and input delay

by Tao, Hongfeng, Zheng, Junhao, Wei, Junyu, Paszke, Wojciech, Rogers, Eric, Stojanovic, Vladimir
Published in Journal of process control (01.12.2023)

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Graph convolutional network soft sensor for process quality prediction

by Jia, Mingwei, Xu, Danya, Yang, Tao, Liu, Yi, Yao, Yuan
Published in Journal of process control (01.03.2023)

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Stochastic linear Model Predictive Control with chance constraints – A review

by Farina, Marcello, Giulioni, Luca, Scattolini, Riccardo
Published in Journal of process control (01.08.2016)

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On Recurrent Neural Networks for learning-based control: Recent results and ideas for future developments

by Bonassi, Fabio, Farina, Marcello, Xie, Jing, Scattolini, Riccardo
Published in Journal of process control (01.06.2022)

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Review of control strategies for improving the energy flexibility provided by heat pump systems in buildings

by Péan, Thibault Q., Salom, Jaume, Costa-Castelló, Ramon
Published in Journal of process control (01.02.2019)

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A tutorial review of economic model predictive control methods

by Ellis, Matthew, Durand, Helen, Christofides, Panagiotis D.
Published in Journal of process control (01.08.2014)

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One-dimensional convolutional auto-encoder-based feature learning for fault diagnosis of multivariate processes

by Chen, Shumei, Yu, Jianbo, Wang, Shijin
Published in Journal of process control (01.03.2020)

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A comparison study of basic data-driven fault diagnosis and process monitoring methods on the benchmark Tennessee Eastman process

by Yin, Shen, Ding, Steven X., Haghani, Adel, Hao, Haiyang, Zhang, Ping
Published in Journal of process control (01.10.2012)

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Cloud-based implementation of white-box model predictive control for a GEOTABS office building: A field test demonstration

by Drgoňa, Ján, Picard, Damien, Helsen, Lieve
Published in Journal of process control (01.04.2020)

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Data-driven soft sensor development based on deep learning technique

by Shang, Chao, Yang, Fan, Huang, Dexian, Lyu, Wenxiang
Published in Journal of process control (01.03.2014)

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Process structure-based recurrent neural network modeling for model predictive control of nonlinear processes

by Wu, Zhe, Rincon, David, Christofides, Panagiotis D.
Published in Journal of process control (01.05.2020)

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Prediction model of end-point phosphorus content in BOF steelmaking process based on PCA and BP neural network

by He, Fei, Zhang, Lingying
Published in Journal of process control (01.06.2018)

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Deep learning for fault-relevant feature extraction and fault classification with stacked supervised auto-encoder

by Wang, Yalin, Yang, Haibing, Yuan, Xiaofeng, Shardt, Yuri A.W., Yang, Chunhua, Gui, Weihua
Published in Journal of process control (01.08.2020)

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Statistical process monitoring as a big data analytics tool for smart manufacturing

by He, Q. Peter, Wang, Jin
Published in Journal of process control (01.07.2018)

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Rebooting data-driven soft-sensors in process industries: A review of kernel methods

by Liu, Yiqi, Xie, Min
Published in Journal of process control (01.05.2020)

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A survey and classification of incipient fault diagnosis approaches

by Safaeipour, H., Forouzanfar, M., Casavola, A.
Published in Journal of process control (01.01.2021)

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Continuous control of a polymerization system with deep reinforcement learning

by Ma, Yan, Zhu, Wenbo, Benton, Michael G., Romagnoli, José
Published in Journal of process control (01.03.2019)

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