Search Results - "CHRISTOFIDES, Panagiotis D"

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  1. 1

    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)
    “…•Methods for the design of economic model predictive control (EMPC) systems.•Discussion of closed-loop stability and performance properties of various EMPC…”
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    Journal Article
  2. 2

    Machine learning‐based predictive control of nonlinear processes. Part I: Theory by Wu, Zhe, Tran, Anh, Rincon, David, Christofides, Panagiotis D.

    Published in AIChE journal (01-11-2019)
    “…This article focuses on the design of model predictive control (MPC) systems for nonlinear processes that utilize an ensemble of recurrent neural network (RNN)…”
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    Journal Article
  3. 3

    Machine‐learning‐based predictive control of nonlinear processes. Part II: Computational implementation by Wu, Zhe, Tran, Anh, Rincon, David, Christofides, Panagiotis D.

    Published in AIChE journal (01-11-2019)
    “…Machine learning is receiving more attention in classical engineering fields, and in particular, recurrent neural networks (RNNs) coupled with ensemble…”
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    Journal Article
  4. 4

    Distributed model predictive control: A tutorial review and future research directions by Christofides, Panagiotis D., Scattolini, Riccardo, Muñoz de la Peña, David, Liu, Jinfeng

    Published in Computers & chemical engineering (05-04-2013)
    “…In this paper, we provide a tutorial review of recent results in the design of distributed model predictive control systems. Our goal is to not only…”
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    Journal Article Conference Proceeding
  5. 5

    Recurrent Neural-Network-Based Model Predictive Control of a Plasma Etch Process by Xiao, Tianqi, Wu, Zhe, Christofides, Panagiotis D, Armaou, Antonios, Ni, Dong

    “…In this article, we propose the development of a recurrent neural network (RNN)-based model predictive controller (MPC) for a plasma etch process on a…”
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    Journal Article
  6. 6

    Machine-learning-based state estimation and predictive control of nonlinear processes by Alhajeri, Mohammed S., Wu, Zhe, Rincon, David, Albalawi, Fahad, Christofides, Panagiotis D.

    Published in Chemical engineering research & design (01-03-2021)
    “…•Design of state estimators using recurrent neural networks from process data.•Design of hybrid state estimators using both process data and first…”
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    Journal Article
  7. 7

    Machine learning-based model predictive control of diffusion-reaction processes by Dodhia, Aarsh, Wu, Zhe, Christofides, Panagiotis D.

    Published in Chemical engineering research & design (01-09-2021)
    “…•Empirical eigenfunction construction from process data.•Neural network modeling of temporal evolution.•Model predictive control using machine learning…”
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    Journal Article
  8. 8

    Microscopic and data-driven modeling and operation of thermal atomic layer etching of aluminum oxide thin films by Yun, Sungil, Tom, Matthew, Luo, Junwei, Orkoulas, Gerassimos, Christofides, Panagiotis D.

    Published in Chemical engineering research & design (01-01-2022)
    “…•Microscopic modeling of atomic layer etching.•Calculation of reaction rate parameters via first-principles.•Computationally-efficient machine learning model…”
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    Journal Article
  9. 9

    Economic Machine-Learning-Based Predictive Control of Nonlinear Systems by Wu, Zhe, Christofides, Panagiotis

    Published in Mathematics (Basel) (01-06-2019)
    “…In this work, a Lyapunov-based economic model predictive control (LEMPC) method is developed to address economic optimality and closed-loop stability of…”
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    Journal Article
  10. 10

    Analysis of forward osmosis desalination via two-dimensional FEM model by SAGIV, Abraham, ZHU, Aihua, CHRISTOFIDES, Panagiotis D, COHEN, Yoram, SEMIAT, Raphael

    Published in Journal of membrane science (01-08-2014)
    “…Forward osmosis (FO) desalination was investigated via 2-D numerical model of the fully coupled hydrodynamics and mass transfer equations. The model was…”
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    Journal Article
  11. 11

    Machine learning-based modeling and operation for ALD of SiO2 thin-films using data from a multiscale CFD simulation by Ding, Yangyao, Zhang, Yichi, Ren, Yi Ming, Orkoulas, Gerassimos, Christofides, Panagiotis D.

    Published in Chemical engineering research & design (01-11-2019)
    “…[Display omitted] •Multiscale computational fluid dynamics (CFD) modeling of ALD reactor.•Machine-learning modeling using multiscale CFD model data.•Use of…”
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    Journal Article
  12. 12

    Multiscale three-dimensional CFD modeling for PECVD of amorphous silicon thin films by Crose, Marquis, Zhang, Weiqi, Tran, Anh, Christofides, Panagiotis D.

    Published in Computers & chemical engineering (08-05-2018)
    “…•Development of a three-dimensional, multiscale computational fluid dynamics (CFD) modeling framework for thin film growth processes.•Efficient parallel…”
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    Journal Article
  13. 13

    Multiscale modeling and run-to-run control of PECVD of thin film solar cells by Crose, Marquis, Kwon, Joseph Sang-Il, Tran, Anh, Christofides, Panagiotis D.

    Published in Renewable energy (01-01-2017)
    “…In this work, we focus on the development of a multiscale modeling and run-to-run control framework with the purpose of improving thin film product quality in…”
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    Journal Article
  14. 14

    Microscopic modeling and optimal operation of plasma enhanced atomic layer deposition by Ding, Yangyao, Zhang, Yichi, Orkoulas, Gerassimos, Christofides, Panagiotis D.

    Published in Chemical engineering research & design (01-07-2020)
    “…•Kinetic Monte-Carlo modeling of PEALD.•Calculation of kMC model parameters via DFT.•Comparison with experimental data.•Neural network modeling for determining…”
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    Journal Article
  15. 15

    Statistical Machine Learning in Model Predictive Control of Nonlinear Processes by Wu, Zhe, Rincon, David, Gu, Quanquan, Christofides, Panagiotis D.

    Published in Mathematics (Basel) (01-08-2021)
    “…Recurrent neural networks (RNNs) have been widely used to model nonlinear dynamic systems using time-series data. While the training error of neural networks…”
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    Journal Article
  16. 16

    Multiscale modeling and operation of PECVD of thin film solar cells by Crose, Marquis, Sang-Il Kwon, Joseph, Nayhouse, Michael, Ni, Dong, Christofides, Panagiotis D.

    Published in Chemical engineering science (02-11-2015)
    “…This work proposes a multiscale modeling and operation framework for plasma-enhanced chemical vapor deposition (PECVD) of thin film silicon solar cells with…”
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    Journal Article
  17. 17

    Real-Time Optimization and Control of Nonlinear Processes Using Machine Learning by Zhang, Zhihao, Wu, Zhe, Rincon, David, Christofides, Panagiotis

    Published in Mathematics (Basel) (01-10-2019)
    “…Machine learning has attracted extensive interest in the process engineering field, due to the capability of modeling complex nonlinear process behavior. This…”
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    Journal Article
  18. 18

    Distributed economic MPC: Application to a nonlinear chemical process network by Chen, Xianzhong, Heidarinejad, Mohsen, Liu, Jinfeng, Christofides, Panagiotis D.

    Published in Journal of process control (01-04-2012)
    “…► Method for the design of distributed economic model predictive control systems. ► Establishment of closed-loop stability properties using rigorous…”
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    Journal Article
  19. 19

    Modeling and control of protein crystal shape and size in batch crystallization by Kwon, Joseph Sang-Il, Nayhouse, Michael, Christofides, Panagiotis D., Orkoulas, Gerassimos

    Published in AIChE journal (01-07-2013)
    “…In this work, the modeling and control of a batch crystallization process used to produce tetragonal hen egg white lysozyme crystals are studied. Two processes…”
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    Journal Article
  20. 20

    Modeling and Control of High-Velocity Oxygen-Fuel (HVOF) Thermal Spray: A Tutorial Review by Li, Mingheng, Christofides, Panagiotis D.

    Published in Journal of thermal spray technology (01-12-2009)
    “…This work provides a tutorial overview of recent research efforts in modeling and control of the high-velocity oxygen-fuel (HVOF) thermal spray process…”
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    Journal Article