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Recursive estimation in constrained nonlinear dynamical systems
Pramod Vachhani, , Vikrant Gangwal,
Published in John Wiley & Sons, Inc.
2005
Volume: 51
   
Issue: 3
Pages: 946 - 959
Abstract
In any modern chemical plant or refinery, process operation and the quality of product depend on the reliability of data used for process monitoring and control. The_task_of improving the quality of data to be consistent with material and energy balances is called reconciliation. Because chemical processes often operate dynamically in nonlinear regimes, techniques such as extended-Kalman filter (EKF) and nonlinear dynamic data reconciliation (NDDR) have been developed for reconciliation. There are various issues that arise with the use of either of these techniques. EKF cannot handle inequality or equality constraints, whereas the NDDR has high computational cost. Therefore, a more efficient and robust method is required for reconciling process measurements and estimating parameters involved in nonlinear dynamic processes. Two solution techniques are presented: recursive nonlinear dynamic data reconciliation (RNDDR) and a combined predictor-corrector optimization (CPCO) method for efficient state and parameter estimation in nonlinear svstems. The proposed approaches combine the efficiency of EKF and the ability of NDDR to handle algebraic inequality and equality constraints. Moreover, the CPCO technique allows deterministic parameter variation, thus relaxing another restriction of EKF where the parameter changes are modeled through a discrete stochastic equation. The proposed techniques are compared against the EKF and the NDDR formulations through simulation studies on a continuous stirred tank reactor and a polymerization reactor. In general, the RNDDR performs as well as the two traditional approaches, whereas the CPCO formulation provides more accurate results than RNDDR at a marginal increase in computational cost. © 2005 American Institute of Chemical Engineers.
About the journal
JournalData powered by TypesetAIChE Journal
PublisherData powered by TypesetJohn Wiley & Sons, Inc.
ISSN00011541
Open AccessNo
Concepts (18)
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    EXTENDED-KALMAN FILTERING (EKF)
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    NONLINEAR DYNAMIC DATA RECONCILIATION (NDDR)
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    NONLINEAR DYNAMIC SYSTEMS
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    Recursive estimation
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    Chemical plants
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    Chemical reactors
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    Computational methods
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    Kalman filtering
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    METAL REFINERIES
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    Optimization
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    Parameter estimation
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    Polymerization
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    Process control
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    Quality control
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    Recursive functions
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    Robustness (control systems)
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    Nonlinear systems
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    System