Fault detection in a single-stage evaporator via parameter estimation using the Kalman filter

Molle, D. T. Dalle; Himmelblau, D. M.

doi:10.1021/ie00072a016

Cited by 25 publications

(10 citation statements)

References 5 publications

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“…Out of the three parameters (r, 91, and q 2 ) that typically appear in a design with one output and two states, the ratios ql/r and qdr were shown to govern the behavior of the estimator for a given chemical component. Because the input noise, w1, is fictitious and is introduced to model unknown variables, these two ratios are in principle adjustable parameters (Dalla Molle and Himmelblau, 1987). We have shown that using elements of control theory and stochastic systems theory they can be simply and uniquely determined.…”

Section: Discussionmentioning

confidence: 99%

Online Estimation of Reaction Rates in Semicontinuous Reactors

Eliçabe¹,

Ozdeger²,

Georgakis³

et al. 1995

Ind. Eng. Chem. Res.

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State estimation techniques are used to on-line estimate reaction rates in well-mixed semicontinuous reactors. The proposed scheme assumes the availability of on-line measurements of the total mass of the reactants in the reactor, and copes with the lack of knowledge of the reaction rate dependence with concentration. Concepts from system theory are used to reduce the degrees of freedom that the pure Kalman filtering design produces. By the use of three examples of semicontinuous emulsion copolymerization, it is shown that accurate estimates of the reaction rates are possible in the presence of inaccurate measurements of the incoming flow rates and much earlier than the establishment of the pseudo-steady-state condition. The proposed technique is applied t o the experimental data collected during the semibatch polymerization of the following ternary systems: (a) acrylonitrile-ethyl acrylate-N-methylacrylamide and (b) butyl acrylate-styrene-acrylic acid.

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Section: Discussionmentioning

confidence: 99%

Online Estimation of Reaction Rates in Semicontinuous Reactors

Eliçabe¹,

Ozdeger²,

Georgakis³

et al. 1995

Ind. Eng. Chem. Res.

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“…A mathematical model of a single-stage evaporator system (Dalle Molle and Himmelblau, 1987) is given as :…”

Section: Example 3: Single-stage Evaporator Systemmentioning

confidence: 99%

Parameter estimation using multiparametric programming for implicit Euler’s method based discretization

Mid

Dua

2019

Chemical Engineering Research and Design

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This work presents a study that aims to compare two discretization methods for solving parameter estimation using multiparametric programming. In our earlier work, parameter estimation using multiparametric programming was presented where model parameters were obtained as an explicit function of measurements. In this method, the nonlinear ordinary equations (ODEs) model was discretized by using explicit Euler's method to obtain algebraic

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“…This is because parameter estimates are in general more sensitive to faults than estimates of the state variables. and thus they are better indications of the degradation of system performance (Dalle Molle and Himmelblau, 1987). Since it is usually possible to associate the assumed malfunctions with changes in the corresponding model parameters, these parameters can be treated as augmented states in the corresponding EKF (Himmelblau, 1978).…”

Section: Fault Observabilitymentioning

confidence: 99%

Simplification techniques for EKF computations in fault diagnosis: Model decomposition

Chang¹,

Hwang²

1998

AIChE Journal

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Fault detection in a single-stage evaporator via parameter estimation using the Kalman filter

Abstract: Because process faults and degradation may lead to inefficient and even unsafe process operation, fault diagnosis has received considerable attention in the literature.

Cited by 25 publications

References 5 publications

Online Estimation of Reaction Rates in Semicontinuous Reactors

Online Estimation of Reaction Rates in Semicontinuous Reactors

Parameter estimation using multiparametric programming for implicit Euler’s method based discretization

Simplification techniques for EKF computations in fault diagnosis: Model decomposition

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