Found: 109
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Integrating dynamic economic optimization and encrypted control for cyber‐resilient operation of nonlinear processes.
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- AIChE Journal, 2024, v. 70, n. 9, p. 1, doi. 10.1002/aic.18509
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Process modeling guides operational variables that affect CO<sub>2</sub> utilization during the accelerated carbonation of concrete.
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- AIChE Journal, 2024, v. 70, n. 5, p. 1, doi. 10.1002/aic.18387
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Encrypted model predictive control design for security to cyberattacks.
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- AIChE Journal, 2023, v. 69, n. 8, p. 1, doi. 10.1002/aic.18104
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Machine‐learning‐based construction of barrier functions and models for safe model predictive control.
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- AIChE Journal, 2022, v. 68, n. 6, p. 1, doi. 10.1002/aic.17456
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Statistical machine‐learning–based predictive control of uncertain nonlinear processes.
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- AIChE Journal, 2022, v. 68, n. 5, p. 1, doi. 10.1002/aic.17642
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Machine learning modeling and predictive control of nonlinear processes using noisy data.
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- AIChE Journal, 2021, v. 67, n. 4, p. 1, doi. 10.1002/aic.17164
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Machine learning‐based distributed model predictive control of nonlinear processes.
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- AIChE Journal, 2020, v. 66, n. 11, p. 1, doi. 10.1002/aic.17013
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A cyber‐secure control‐detector architecture for nonlinear processes.
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- AIChE Journal, 2020, v. 66, n. 5, p. 1, doi. 10.1002/aic.16907
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Machine‐learning‐based predictive control of nonlinear processes. Part II: Computational implementation.
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- AIChE Journal, 2019, v. 65, n. 11, p. N.PAG, doi. 10.1002/aic.16734
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Machine learning‐based predictive control of nonlinear processes. Part I: Theory.
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- AIChE Journal, 2019, v. 65, n. 11, p. N.PAG, doi. 10.1002/aic.16729
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Run‐to‐run control of PECVD systems: Application to a multiscale three‐dimensional CFD model of silicon thin film deposition.
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- AIChE Journal, 2019, v. 65, n. 7, p. N.PAG, doi. 10.1002/aic.16400
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Economic model predictive control of stochastic nonlinear systems.
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- AIChE Journal, 2018, v. 64, n. 9, p. 3312, doi. 10.1002/aic.16167
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Optimal operation of batch enantiomer crystallization: From ternary diagrams to predictive control.
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- AIChE Journal, 2018, v. 64, n. 5, p. 1618, doi. 10.1002/aic.16028
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Distributed economic model predictive control for operational safety of nonlinear processes.
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- AIChE Journal, 2017, v. 63, n. 8, p. 3404, doi. 10.1002/aic.15710
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An economic model predictive control approach to integrated production management and process operation.
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- AIChE Journal, 2017, v. 63, n. 6, p. 1892, doi. 10.1002/aic.15553
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Error-triggered on-line model identification for model-based feedback control.
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- AIChE Journal, 2017, v. 63, n. 3, p. 949, doi. 10.1002/aic.15430
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A feedback control framework for safe and economically-optimal operation of nonlinear processes.
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- AIChE Journal, 2016, v. 62, n. 7, p. 2391, doi. 10.1002/aic.15222
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Actuator stiction compensation via model predictive control for nonlinear processes.
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- AIChE Journal, 2016, v. 62, n. 6, p. 2004, doi. 10.1002/aic.15171
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Economic model predictive control of nonlinear time-delay systems: Closed-loop stability and delay compensation.
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- AIChE Journal, 2015, v. 61, n. 12, p. 4152, doi. 10.1002/aic.14964
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Real-time preventive sensor maintenance using robust moving horizon estimation and economic model predictive control.
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- AIChE Journal, 2015, v. 61, n. 10, p. 3374, doi. 10.1002/aic.14960
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On identification of well-conditioned nonlinear systems: Application to economic model predictive control of nonlinear processes.
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- AIChE Journal, 2015, v. 61, n. 10, p. 3353, doi. 10.1002/aic.14942
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Economic model predictive control of nonlinear process systems using empirical models.
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- AIChE Journal, 2015, v. 61, n. 3, p. 816, doi. 10.1002/aic.14683
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Real-time economic model predictive control of nonlinear process systems.
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- AIChE Journal, 2015, v. 61, n. 2, p. 555, doi. 10.1002/aic.14673
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Selection of control configurations for economic model predictive control systems.
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- AIChE Journal, 2014, v. 60, n. 9, p. 3230, doi. 10.1002/aic.14514
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Encrypted Model Predictive Control of a Nonlinear Chemical Process Network.
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- Processes, 2023, v. 11, n. 8, p. 2501, doi. 10.3390/pr11082501
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Reverse osmosis desalination with high permeability membranes -- Cost optimization and research needs.
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- Desalination & Water Treatment, 2010, v. 15, n. 1-3, p. 256, doi. 10.5004/dwt.2010.1763
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Data-based monitoring and reconfiguration of a distributed model predictive control system.
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- International Journal of Robust & Nonlinear Control, 2012, v. 22, n. 1, p. 68, doi. 10.1002/rnc.1759
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Predictive control of parabolic PDEs with state and control constraints.
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- International Journal of Robust & Nonlinear Control, 2006, v. 16, n. 16, p. 749, doi. 10.1002/rnc.1097
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Fault-tolerant control of nonlinear processes: performance-based reconfiguration and robustness.
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- International Journal of Robust & Nonlinear Control, 2006, v. 16, n. 3, p. 91, doi. 10.1002/rnc.1045
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Hybrid predictive control of nonlinear systems: method and applications to chemical processes.
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- International Journal of Robust & Nonlinear Control, 2004, v. 14, n. 2, p. 199, doi. 10.1002/rnc.870
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Distributed nonlinear control of diffusionreaction processes.
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- International Journal of Robust & Nonlinear Control, 2004, v. 14, n. 2, p. 133, doi. 10.1002/rnc.867
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Robust inverse optimal control laws for nonlinear systems.
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- International Journal of Robust & Nonlinear Control, 2003, v. 13, n. 15, p. 1371, doi. 10.1002/rnc.860
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Robust detection of intermittent multiplicative sensor fault.
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- Asian Journal of Control, 2021, v. 23, n. 1, p. 463, doi. 10.1002/asjc.2241
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Event‐triggered filtering and intermittent fault detection for time‐varying systems with stochastic parameter uncertainty and sensor saturation.
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- International Journal of Robust & Nonlinear Control, 2018, v. 28, n. 16, p. 4666, doi. 10.1002/rnc.4276
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Real-Time Optimization and Control of Nonlinear Processes Using Machine Learning.
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- Mathematics (2227-7390), 2019, v. 7, n. 10, p. 890, doi. 10.3390/math7100890
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Economic Machine-Learning-Based Predictive Control of Nonlinear Systems.
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- Mathematics (2227-7390), 2019, v. 7, n. 6, p. 494, doi. 10.3390/math7060494
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Detecting and Handling Cyber-Attacks in Model Predictive Control of Chemical Processes.
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- Mathematics (2227-7390), 2018, v. 6, n. 10, p. 173, doi. 10.3390/math6100173
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Safeness Index-Based Economic Model Predictive Control of Stochastic Nonlinear Systems.
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- Mathematics (2227-7390), 2018, v. 6, n. 5, p. 69, doi. 10.3390/math6050069
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Integrating run-to-run control with feedback control for a spatial atomic layer etching reactor.
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- Chemical Engineering Research & Design: Transactions of the Institution of Chemical Engineers Part A, 2024, v. 203, p. 1, doi. 10.1016/j.cherd.2024.01.030
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Sparse identification modeling and predictive control of wafer temperature in an atomic layer etching reactor.
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- Chemical Engineering Research & Design: Transactions of the Institution of Chemical Engineers Part A, 2024, v. 202, p. 1, doi. 10.1016/j.cherd.2023.12.024
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Encrypted decentralized model predictive control of nonlinear processes with delays.
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- Chemical Engineering Research & Design: Transactions of the Institution of Chemical Engineers Part A, 2023, v. 200, p. 312, doi. 10.1016/j.cherd.2023.10.041
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Machine learning-based predictive control using on-line model linearization: Application to an experimental electrochemical reactor.
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- Chemical Engineering Research & Design: Transactions of the Institution of Chemical Engineers Part A, 2023, v. 197, p. 721, doi. 10.1016/j.cherd.2023.08.017
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Real-time adaptive sparse-identification-based predictive control of nonlinear processes.
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- Chemical Engineering Research & Design: Transactions of the Institution of Chemical Engineers Part A, 2023, v. 196, p. 750, doi. 10.1016/j.cherd.2023.07.011
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Machine learning-based ethylene and carbon monoxide estimation, real-time optimization, and multivariable feedback control of an experimental electrochemical reactor.
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- Chemical Engineering Research & Design: Transactions of the Institution of Chemical Engineers Part A, 2023, v. 191, p. 658, doi. 10.1016/j.cherd.2023.02.003
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On generalization error of neural network models and its application to predictive control of nonlinear processes.
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- Chemical Engineering Research & Design: Transactions of the Institution of Chemical Engineers Part A, 2023, v. 189, p. 664, doi. 10.1016/j.cherd.2022.12.001
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Atomistic-mesoscopic modeling of area-selective thermal atomic layer deposition.
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- Chemical Engineering Research & Design: Transactions of the Institution of Chemical Engineers Part A, 2022, v. 188, p. 271, doi. 10.1016/j.cherd.2022.09.051
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Physics-informed machine learning modeling for predictive control using noisy data.
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- Chemical Engineering Research & Design: Transactions of the Institution of Chemical Engineers Part A, 2022, v. 186, p. 34, doi. 10.1016/j.cherd.2022.07.035
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Machine learning-based ethylene concentration estimation, real-time optimization and feedback control of an experimental electrochemical reactor.
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- Chemical Engineering Research & Design: Transactions of the Institution of Chemical Engineers Part A, 2022, v. 185, p. 87, doi. 10.1016/j.cherd.2022.06.044
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Multivariable run-to-run control of thermal atomic layer etching of aluminum oxide thin films.
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- Chemical Engineering Research & Design: Transactions of the Institution of Chemical Engineers Part A, 2022, v. 182, p. 1, doi. 10.1016/j.cherd.2022.03.039
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Process structure-based recurrent neural network modeling for predictive control: A comparative study.
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- Chemical Engineering Research & Design: Transactions of the Institution of Chemical Engineers Part A, 2022, v. 179, p. 77, doi. 10.1016/j.cherd.2021.12.046
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