1
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Chen L, Li HX, Yang HD. Spatiotemporal Modeling for Distributed Parameter System under Sparse Sensing. Ind Eng Chem Res 2020. [DOI: 10.1021/acs.iecr.0c02120] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Liqun Chen
- Department of Systems Engineering and Engineering Management, City University of Hong Kong, Hong Kong, China
- State Key Laboratory of High Performance Complex Manufacturing, Central South University, Changsha, Hunan, China
| | - Han-Xiong Li
- Department of Systems Engineering and Engineering Management, City University of Hong Kong, Hong Kong, China
| | - Hai-Dong Yang
- Guangdong Engineering Research Center for Green Manufacturing and Energy Efficiency Optimization, Guangdong University of Technology, Guangdong, China
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2
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Qing X, Jin J, Niu Y, Zhao S. Time–space
coupled learning method for model reduction of distributed parameter systems with
encoder‐decoder
and
RNN. AIChE J 2020. [DOI: 10.1002/aic.16251] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Affiliation(s)
- Xiangyun Qing
- Key Laboratory of Advanced Control and Optimization for Chemical Processes (East China University of Science and Technology), Ministry of EducationEast China University of Science and Technology Shanghai China
| | - Jing Jin
- Key Laboratory of Advanced Control and Optimization for Chemical Processes (East China University of Science and Technology), Ministry of EducationEast China University of Science and Technology Shanghai China
| | - Yugang Niu
- Key Laboratory of Advanced Control and Optimization for Chemical Processes (East China University of Science and Technology), Ministry of EducationEast China University of Science and Technology Shanghai China
| | - Shuangliang Zhao
- State Key Laboratory of Chemical Engineering and School of Chemical EngineeringEast China University of Science and Technology Shanghai China
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3
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Efficient reduced order controller design for dissipative PDE systems with strong convective phenomena. Chem Eng Res Des 2018. [DOI: 10.1016/j.cherd.2018.09.025] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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4
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Siddhamshetty P, Wu K, Kwon JSI. Optimization of simultaneously propagating multiple fractures in hydraulic fracturing to achieve uniform growth using data-based model reduction. Chem Eng Res Des 2018. [DOI: 10.1016/j.cherd.2018.06.015] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
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5
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Approximate Dynamic Programming Based Control of Proppant Concentration in Hydraulic Fracturing. MATHEMATICS 2018. [DOI: 10.3390/math6080132] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Hydraulic fracturing has played a crucial role in enhancing the extraction of oil and gas from deep underground sources. The two main objectives of hydraulic fracturing are to produce fractures with a desired fracture geometry and to achieve the target proppant concentration inside the fracture. Recently, some efforts have been made to accomplish these objectives by the model predictive control (MPC) theory based on the assumption that the rock mechanical properties such as the Young’s modulus are known and spatially homogenous. However, this approach may not be optimal if there is an uncertainty in the rock mechanical properties. Furthermore, the computational requirements associated with the MPC approach to calculate the control moves at each sampling time can be significantly high when the underlying process dynamics is described by a nonlinear large-scale system. To address these issues, the current work proposes an approximate dynamic programming (ADP) based approach for the closed-loop control of hydraulic fracturing to achieve the target proppant concentration at the end of pumping. ADP is a model-based control technique which combines a high-fidelity simulation and function approximator to alleviate the “curse-of-dimensionality” associated with the traditional dynamic programming (DP) approach. A series of simulations results is provided to demonstrate the performance of the ADP-based controller in achieving the target proppant concentration at the end of pumping at a fraction of the computational cost required by MPC while handling the uncertainty in the Young’s modulus of the rock formation.
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6
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Siddhamshetty P, Yang S, Kwon JSI. Modeling of hydraulic fracturing and designing of online pumping schedules to achieve uniform proppant concentration in conventional oil reservoirs. Comput Chem Eng 2018. [DOI: 10.1016/j.compchemeng.2017.10.032] [Citation(s) in RCA: 41] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
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7
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Yang M, Armaou A. Revisiting APOD accuracy for nonlinear control of transport reaction processes: A spatially discrete approach. Chem Eng Sci 2018. [DOI: 10.1016/j.ces.2017.12.037] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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8
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Model-based feedback control of oil production in oil-rim reservoirs under gas coning conditions. Comput Chem Eng 2018. [DOI: 10.1016/j.compchemeng.2018.02.001] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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9
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Yang M, Armaou A. Synthesis of Equation-Free Control Structures for Dissipative Distributed Parameter Systems Using Proper Orthogonal Decomposition and Discrete Empirical Interpolation Methods. Ind Eng Chem Res 2017. [DOI: 10.1021/acs.iecr.7b02322] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Manda Yang
- Department
of Chemical Engineering, The Pennsylvania State University, University Park, Pennsylvania 16802, United States
| | - Antonios Armaou
- Department
of Chemical Engineering, The Pennsylvania State University, University Park, Pennsylvania 16802, United States
- Department
of Mechanical Engineering, Wenzhou University, Zhejiang, China
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10
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Dynamic shaping of transport–reaction processes with a combined sliding mode controller and Luenberger-type dynamic observer design. Chem Eng Sci 2015. [DOI: 10.1016/j.ces.2015.07.054] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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11
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Pourkargar DB, Armaou A. Design of APOD-based switching dynamic observers and output feedback control for a class of nonlinear distributed parameter systems. Chem Eng Sci 2015. [DOI: 10.1016/j.ces.2015.02.032] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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12
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Babaei Pourkargar D, Armaou A. Control of spatially distributed processes with unknown transport-reaction parameters via two layer system adaptations. AIChE J 2015. [DOI: 10.1002/aic.14852] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
| | - Antonios Armaou
- Dept. of Chemical Engineering; The Pennsylvania State University; University Park; PA 16802
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13
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Pourkargar DB, Armaou A. APOD-based control of linear distributed parameter systems under sensor/controller communication bandwidth limitations. AIChE J 2014. [DOI: 10.1002/aic.14640] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Affiliation(s)
| | - Antonios Armaou
- Dept. of Chemical Engineering; The Pennsylvania State University; University Park PA 16802
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14
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Pourkargar DB, Armaou A. Geometric output tracking of nonlinear distributed parameter systems via adaptive model reduction. Chem Eng Sci 2014. [DOI: 10.1016/j.ces.2014.05.030] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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