State and parameter estimation for adsorption columns by nonlinear distributed parameter state observers

Mangold, Michael; Lauschke, G; Schaffner, Johanna; Zeitz, Μ.; Gilles, E. D.

doi:10.1016/0959-1524(94)85008-9

Cited by 37 publications

(7 citation statements)

References 3 publications

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“…in all the axial coordinate z where the equations are discretised, but they are known only for the m points were the solid temperature is measured. Here, according to the method proposed by Mangold et al (1994), exponential weighting functions will be used to approximate the error profiles:…”

Section: Observer Designmentioning

confidence: 99%

Observer design for the Selective Catalytic Reduction of NOx in a loop reactor

Fissore

Pisano

Barresi

2007

Chemical Engineering Journal

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The aim of this work is to show how to design a soft-sensor to monitor the Selective Catalytic Reduction (SCR) of NOx with NH3 in a loop reactor, i.e. a loop-shape system made of N units with periodical variation of the feed position. The design procedure of Zeitz (1977) is used and, even if the design procedure remains basically heuristic, some general guidelines to design the observer are given. The proposed observer is demonstrated to allow for a quick and reliable estimation of the inlet NOx concentration, as well as of the outlet reactants conversion and of the temperature profiles in the reactors, using some temperature measurements in the reactor, even when the NOx and the NH3 concentration in the feed change. The results may be used for control purposes, thus avoiding expensive hardware sensors and time consuming on-line measurements.

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Section: Observer Designmentioning

confidence: 99%

Observer design for the Selective Catalytic Reduction of NOx in a loop reactor

Fissore

Pisano

Barresi

2007

Chemical Engineering Journal

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“…For nonlinear DPSs, state estimation is an acute problem as the Dyhia Benameur , Ahmed Maidi , Saïd Djennoune , Jean-Pierre Corriou presence of strong nonlinearities [30,1] that capture important phenomena like diffusion makes the observability analysis, the observer design and the convergence analysis much more difficult. This explains the few contributions reported in the literature [2,13,17,18,32].…”

Section: Introductionmentioning

confidence: 76%

Observer design for a nonlinear diffusion system based on the Kirchhoff transformation

Benameur

Maidi

Djennoune

et al. 2017

Int. J. Dynam. Control

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This paper deals with the state estimation for a nonlinear diffusion system. An observer that reconstructs the whole state, from the available measurements, is proposed based on an equivalent linear diffusion model obtained using the Kirchhoff tangent transformation. This bijective mapping allows to apply the available and powerful state estimation theory of linear distributed parameter systems and simplifies the observer design. Hence, an observer can be designed for the obtained equivalent linear diffusion system and by using the Kirchhoff transformation, the whole state of the original nonlinear diffusion system is recovered. The observability analysis of the nonlinear diffusion system and the convergence of the proposed observer are also investigated based on the equivalent linear diffusion system. The effectiveness of the proposed observer is shown, through numerical simulation runs, in the case of a heated steel rod by considering both an uniformly distributed and a punctual boundary sensing. Keywords distributed parameter system • nonlinear diffusion • partial differential equation • Kirchhoff tangent transformation • state estimation • observer.

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“…Christofides and his co-workers made extensive contributions on the control and estimation of distributed parameter systems with applications to chemical processes, especially in predictive and robust control for transport-reaction processes [26][27][28][29][30]. Zeitz and his co-workers proposed the observability canonical form and extended Luenberger observer for nonlinear distributed parameter systems, which were further applied to state and parameter estimation of adsorption processes and chemical reactors [31][32][33][34][35]. Moreover, interesting work on distributed parameter observer designs for layering granulation, crystallization, and reaction-diffusion processes can be found in [36][37][38].…”

Section: Introductionmentioning

confidence: 99%

Discrete-Time Kalman Filter Design for Linear Infinite-Dimensional Systems

Xie

Dubljević

2019

Processes

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As the optimal linear filter and estimator, the Kalman filter has been extensively utilized for state estimation and prediction in the realm of lumped parameter systems. However, the dynamics of complex industrial systems often vary in both spatial and temporal domains, which take the forms of partial differential equations (PDEs) and/or delay equations. State estimation for these systems is quite challenging due to the mathematical complexity. This work addresses discrete-time Kalman filter design and realization for linear distributed parameter systems. In particular, the structural- and energy-preserving Crank–Nicolson framework is applied for model time discretization without spatial approximation or model order reduction. In order to ensure the time instance consistency in Kalman filter design, a new discrete model configuration is derived. To verify the feasibility of the proposed design, two widely-used PDEs models are considered, i.e., a pipeline hydraulic model and a 1D boundary damped wave equation.

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State and parameter estimation for adsorption columns by nonlinear distributed parameter state observers

Cited by 37 publications

References 3 publications

Observer design for the Selective Catalytic Reduction of NOx in a loop reactor

Observer design for the Selective Catalytic Reduction of NOx in a loop reactor

Observer design for a nonlinear diffusion system based on the Kirchhoff transformation

Discrete-Time Kalman Filter Design for Linear Infinite-Dimensional Systems

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