Estimation of Spatial Concentration Profiles in a Plug Flow Reactor using Reduced Dimensional Models Article Swipe
Gaurav Seth
,
Sachin C. Patwardhan
,
Mani Bhushan
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1016/j.ifacol.2020.06.007
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1016/j.ifacol.2020.06.007
Efficient monitoring and control of a plug flow reactor system requires knowledge of temporal variations of spatial profiles of concentrations. However, estimating the state profiles in spatial domain requires discretization of the governing PDEs at a large number of spatial grid points, which results in high order DAE systems. Computational cost associated with solving these DAEs makes them unattractive candidates for development of advanced on-line monitoring and control schemes. In this work, a novel method for reconstructing spatial profiles of state variables is proposed, which exploits the fact that orthogonal collocation based discretization of PDEs employs time-dependent interpolation polynomials as approximate solutions. A reduced-order approximation of PDE system is developed using Lagrange interpolation polynomials and further used to develop a reduced dimensional extended Kalman filter (EKF). States estimated using the reduced-order EKF, in combination with Lagrange polynomials, are used to construct estimates of spatial profiles of state variables. The proposed approach facilitates handling of measurements available from sensors placed at arbitrary spatial locations other than the collocation points. The performance of proposed reduced-order observer is evaluated via simulation studies performed on a benchmark counter-current plug flow reactor system. Analysis of the simulation results reveals that the proposed approach is capable of generating state profile estimates that are comparable to profile estimates obtained using a high dimensional observer with a significant reduction in the computational cost.
Related Topics
Concepts
Discretization
Lagrange polynomial
Orthogonal collocation
Extended Kalman filter
Interpolation (computer graphics)
Collocation (remote sensing)
Control theory (sociology)
Kalman filter
Observer (physics)
Multivariate interpolation
Lagrange multiplier
Computer science
Mathematics
Mathematical optimization
Algorithm
Applied mathematics
Collocation method
Polynomial
Frame (networking)
Ordinary differential equation
Mathematical analysis
Bilinear interpolation
Differential equation
Statistics
Machine learning
Control (management)
Telecommunications
Artificial intelligence
Physics
Quantum mechanics
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.ifacol.2020.06.007
- OA Status
- diamond
- Cited By
- 3
- References
- 11
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3048763330
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3048763330Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1016/j.ifacol.2020.06.007Digital Object Identifier
- Title
-
Estimation of Spatial Concentration Profiles in a Plug Flow Reactor using Reduced Dimensional ModelsWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2020Year of publication
- Publication date
-
2020-01-01Full publication date if available
- Authors
-
Gaurav Seth, Sachin C. Patwardhan, Mani BhushanList of authors in order
- Landing page
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https://doi.org/10.1016/j.ifacol.2020.06.007Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
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https://doi.org/10.1016/j.ifacol.2020.06.007Direct OA link when available
- Concepts
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Discretization, Lagrange polynomial, Orthogonal collocation, Extended Kalman filter, Interpolation (computer graphics), Collocation (remote sensing), Control theory (sociology), Kalman filter, Observer (physics), Multivariate interpolation, Lagrange multiplier, Computer science, Mathematics, Mathematical optimization, Algorithm, Applied mathematics, Collocation method, Polynomial, Frame (networking), Ordinary differential equation, Mathematical analysis, Bilinear interpolation, Differential equation, Statistics, Machine learning, Control (management), Telecommunications, Artificial intelligence, Physics, Quantum mechanicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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3Total citation count in OpenAlex
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2024: 1, 2023: 1, 2022: 1Per-year citation counts (last 5 years)
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11Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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