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1
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Shao Y, Ma J, Zavala VM. A spatial superstructure approach to the optimal design of modular processes and supply chains. Comput Chem Eng 2022. [DOI: 10.1016/j.compchemeng.2022.108102] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
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2
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Zhao T, Zheng Y, Wu Z. Feature selection-based machine learning modeling for distributed model predictive control of nonlinear processes. Comput Chem Eng 2022. [DOI: 10.1016/j.compchemeng.2022.108074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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3
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Du J, Chen J, Li J, Johansen TA. Multiple Model Predictive Control for Nonlinear Systems Based on Self-Balanced Multimodel Decomposition. Ind Eng Chem Res 2021. [DOI: 10.1021/acs.iecr.1c02426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Jingjing Du
- College of Internet of Things Engineering, Hohai University, Changzhou 213022, China
| | - Junfeng Chen
- College of Internet of Things Engineering, Hohai University, Changzhou 213022, China
| | - Jian Li
- College of Internet of Things Engineering, Hohai University, Changzhou 213022, China
| | - Tor Arne Johansen
- Department of Engineering Cybernetics, Norwegian University of Science and Technology, NO 7491 Trondheim, Norway
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4
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Tang W, Daoutidis P. Coordinating distributed MPC efficiently on a plantwide scale: The Lyapunov envelope algorithm. Comput Chem Eng 2021. [DOI: 10.1016/j.compchemeng.2021.107532] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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5
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Mitrai I, Tang W, Daoutidis P. Stochastic blockmodeling for learning the structure of optimization problems. AIChE J 2021. [DOI: 10.1002/aic.17415] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Affiliation(s)
- Ilias Mitrai
- Department of Chemical Engineering and Materials Science University of Minnesota Minneapolis Minnesota USA
| | - Wentao Tang
- Projects and Technology Shell Global Solutions (U.S.) Inc. Houston Texas USA
| | - Prodromos Daoutidis
- Department of Chemical Engineering and Materials Science University of Minnesota Minneapolis Minnesota USA
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6
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Narasimhan S, El‐Farra NH, Ellis MJ. Detectability‐based
controller design screening for processes under multiplicative cyberattacks. AIChE J 2021. [DOI: 10.1002/aic.17430] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Affiliation(s)
- Shilpa Narasimhan
- Department of Chemical Engineering University of California Davis California USA
| | - Nael H. El‐Farra
- Department of Chemical Engineering University of California Davis California USA
| | - Matthew J. Ellis
- Department of Chemical Engineering University of California Davis California USA
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7
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Yewale A, Methekar R, Agrawal S. Multiple model-based control of multi variable continuous microbial fuel cell (CMFC) using machine learning approaches. Comput Chem Eng 2020. [DOI: 10.1016/j.compchemeng.2020.106884] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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8
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Yin X, Liu J. Distributed state estimation for a class of nonlinear processes based on high-gain observers. Chem Eng Res Des 2020. [DOI: 10.1016/j.cherd.2020.05.008] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
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9
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Ravi A, Kaisare NS. Distributed output feedback control for multi-unit system with delayed multirate measurements. Comput Chem Eng 2020. [DOI: 10.1016/j.compchemeng.2020.106879] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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10
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Abstract
We review the impact of control systems and strategies on the energy efficiency of chemical processes. We show that, in many ways, good control performance is a necessary but not sufficient condition for energy efficiency. The direct effect of process control on energy efficiency is manyfold: Reducing output variability allows for operating chemical plants closer to their limits, where the energy/economic optima typically lie. Further, good control enables novel, transient operating strategies, such as conversion smoothing and demand response. Indirectly, control systems are key to the implementation and operation of more energy-efficient plant designs, as dictated by the process integration and intensification paradigms. These conclusions are supported with references to numerous examples from the literature.
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Affiliation(s)
- Jodie M Simkoff
- McKetta Department of Chemical Engineering, The University of Texas at Austin, Austin, Texas 78712, USA; , , , ,
| | - Fernando Lejarza
- McKetta Department of Chemical Engineering, The University of Texas at Austin, Austin, Texas 78712, USA; , , , ,
| | - Morgan T Kelley
- McKetta Department of Chemical Engineering, The University of Texas at Austin, Austin, Texas 78712, USA; , , , ,
| | - Calvin Tsay
- McKetta Department of Chemical Engineering, The University of Texas at Austin, Austin, Texas 78712, USA; , , , ,
| | - Michael Baldea
- McKetta Department of Chemical Engineering, The University of Texas at Austin, Austin, Texas 78712, USA; , , , ,
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11
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Stevenson Z, Fukasawa R, Ricardez-Sandoval L. A Dynamic Approach to Selecting Time Points for Short-Term Scheduling with Application to Multipurpose Facilities. Ind Eng Chem Res 2020. [DOI: 10.1021/acs.iecr.0c00472] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Zachariah Stevenson
- Department of Combinatorics and Optimization, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada
| | - Ricardo Fukasawa
- Department of Combinatorics and Optimization, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada
| | - Luis Ricardez-Sandoval
- Department of Chemical Engineering, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada
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12
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Shao Y, Zavala VM. Modularity measures: Concepts, computation, and applications to manufacturing systems. AIChE J 2020. [DOI: 10.1002/aic.16965] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Affiliation(s)
- Yue Shao
- Department of Chemical and Biological EngineeringUniversity of Wisconsin‐Madison Madison Wisconsin USA
| | - Victor M. Zavala
- Department of Chemical and Biological EngineeringUniversity of Wisconsin‐Madison Madison Wisconsin USA
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13
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Zhang L, Yin X, Liu J. Complex system decomposition for distributed state estimation based on weighted graph. Chem Eng Res Des 2019. [DOI: 10.1016/j.cherd.2019.08.015] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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14
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Daoutidis P, Allman A, Khatib S, Moharir MA, Palys MJ, Pourkargar DB, Tang W. Distributed decision making for intensified process systems. Curr Opin Chem Eng 2019. [DOI: 10.1016/j.coche.2018.12.007] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
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15
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Daoutidis P, Tang W, Allman A. Decomposition of control and optimization problems by network structure: Concepts, methods, and inspirations from biology. AIChE J 2019. [DOI: 10.1002/aic.16708] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Affiliation(s)
- Prodromos Daoutidis
- Department of Chemical Engineering and Materials Science University of Minnesota Minneapolis Minnesota
| | - Wentao Tang
- Department of Chemical Engineering and Materials Science University of Minnesota Minneapolis Minnesota
| | - Andrew Allman
- Department of Chemical Engineering and Materials Science University of Minnesota Minneapolis Minnesota
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16
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Distributed control and optimization of process system networks: A review and perspective. Chin J Chem Eng 2019. [DOI: 10.1016/j.cjche.2018.08.027] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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17
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Zhang A, Yin X, Liu S, Zeng J, Liu J. Distributed economic model predictive control of wastewater treatment plants. Chem Eng Res Des 2019. [DOI: 10.1016/j.cherd.2018.10.039] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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18
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Yin X, Liu J. Subsystem decomposition of process networks for simultaneous distributed state estimation and control. AIChE J 2018. [DOI: 10.1002/aic.16426] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Affiliation(s)
- Xunyuan Yin
- Dept. of Chemical and Materials EngineeringUniversity of Alberta Edmonton Alberta, T6G 1H9 Canada
| | - Jinfeng Liu
- Dept. of Chemical and Materials EngineeringUniversity of Alberta Edmonton Alberta, T6G 1H9 Canada
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