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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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Gray-box Soft Sensors in Process Industry: Current Practice, and Future Prospects in Era of Big Data. Processes (Basel) 2020. [DOI: 10.3390/pr8020243] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Virtual sensors, or soft sensors, have greatly contributed to the evolution of the sensing systems in industry. The soft sensors are process models having three fundamental categories, namely white-box (WB), black-box (BB) and gray-box (GB) models. WB models are based on process knowledge while the BB models are developed using data collected from the process. The GB models integrate the WB and BB models for addressing the concerns, i.e., accuracy and intuitiveness, of industrial operators. In this work, various design aspects of the GB models are discussed followed by their application in the process industry. In addition, the changes in the data-driven part of the GB models in the context of enormous amount of process data collected in Industry 4.0 are elaborated.
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Fatoorehchi H, Abolghasemi H, Zarghami R. An Efficient Measure for Quantification of Nonlinearity in Chemical Engineering Processes Based on I/O Steady-State Loci. CHEM ENG COMMUN 2015. [DOI: 10.1080/00986445.2014.962689] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
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Tan GT, Huzmezan M, Kwok KE. On Measuring Closed-Loop Non-Linearity: A Topological Approach. CAN J CHEM ENG 2008. [DOI: 10.1002/cjce.5450850411] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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Rojas OJ, Bao J, Lee PL. Linear Control of Nonlinear Processes: The Regions of Steady-state Attainability. Ind Eng Chem Res 2006. [DOI: 10.1021/ie051226j] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Osvaldo J. Rojas
- School of Chemical Engineering and Industrial Chemistry, The University of New South Wales, Sydney NSW 2052, Australia, and Chancellery, Level 2, 160 Currie Street, The University of South Australia, Adelaide SA 5000, Australia
| | - Jie Bao
- School of Chemical Engineering and Industrial Chemistry, The University of New South Wales, Sydney NSW 2052, Australia, and Chancellery, Level 2, 160 Currie Street, The University of South Australia, Adelaide SA 5000, Australia
| | - Peter L. Lee
- School of Chemical Engineering and Industrial Chemistry, The University of New South Wales, Sydney NSW 2052, Australia, and Chancellery, Level 2, 160 Currie Street, The University of South Australia, Adelaide SA 5000, Australia
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Eker SA, Nikolaou M. Linear control of nonlinear systems: Interplay between nonlinearity and feedback. AIChE J 2006. [DOI: 10.1002/aic.690480912] [Citation(s) in RCA: 30] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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9
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Nikolaou M, Misra P. Linear control of nonlinear processes: recent developments and future directions. Comput Chem Eng 2003. [DOI: 10.1016/s0098-1354(03)00036-x] [Citation(s) in RCA: 30] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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Hernjak N, Doyle FJ. Correlation of Process Nonlinearity with Closed-Loop Disturbance Rejection. Ind Eng Chem Res 2003. [DOI: 10.1021/ie020910k] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Nicholas Hernjak
- Department of Chemical Engineering, University of Delaware, Newark, Delaware 19716, and Department of Chemical Engineering, University of California, Santa Barbara, Santa Barbara, California 93106
| | - Francis J. Doyle
- Department of Chemical Engineering, University of Delaware, Newark, Delaware 19716, and Department of Chemical Engineering, University of California, Santa Barbara, Santa Barbara, California 93106
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Hahn J, Edgar TF. A Gramian Based Approach to Nonlinearity Quantification and Model Classification. Ind Eng Chem Res 2001. [DOI: 10.1021/ie010155v] [Citation(s) in RCA: 37] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Juergen Hahn
- Department of Chemical Engineering, The University of Texas at Austin, Austin, Texas 78712-1062
| | - Thomas F. Edgar
- Department of Chemical Engineering, The University of Texas at Austin, Austin, Texas 78712-1062
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Harris KR, Colantonio M, Palazoğlu A. On the computation of a nonlinearity measure using functional expansions. Chem Eng Sci 2000. [DOI: 10.1016/s0009-2509(99)00514-x] [Citation(s) in RCA: 22] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Gao F, Wang F, Li M. An Analytical Predictive Control Law for a Class of Nonlinear Processes. Ind Eng Chem Res 2000. [DOI: 10.1021/ie9902176] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Furong Gao
- Department of Chemical Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
| | - Fuli Wang
- Department of Chemical Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
| | - Mingzhong Li
- Department of Chemical Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
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Verazaluce-García JC, Flores-Tlacuahuac A, Saldívar-Guerra E. Steady-State Nonlinear Bifurcation Analysis of a High-Impact Polystyrene Continuous Stirred Tank Reactor. Ind Eng Chem Res 2000. [DOI: 10.1021/ie990560a] [Citation(s) in RCA: 28] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
| | - Antonio Flores-Tlacuahuac
- Departamento de Ciencias, Universidad Iberoamericana, Prolongación Paseo de la Reforma 880, México DF 01210, México
| | - Enrique Saldívar-Guerra
- Centro de Investigacion y Desarrollo Tecnológico (CID), Avenida de los Sauces 87-6, Lerma, Edo de México 52000, México
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Stack AJ, Doyle FJ. The optimal control structure: an approach to measuring control-law nonlinearity. Comput Chem Eng 1997. [DOI: 10.1016/s0098-1354(96)00339-0] [Citation(s) in RCA: 35] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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