Dynamic estimation of temperature and concentration profiles in a packed bed reactor

Windes, Larry C.; Çınar, Ali; Ray, W. Harmon

doi:10.1016/0009-2509(89)85144-9

Cited by 25 publications

(9 citation statements)

References 27 publications

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“…Due to the strongly non-linear characteristics of the system under investigation, the state estimation approaches, based on linearization techniques and lumping (via the orthogonal collocation method) that are usually adopted for nonlinear distributed parameter fixed bed reactors, are not suitable. Moreover, the application of the extended Kalman filter to the full non-linear distributed parameters model of the reactor results in a large number of differential equations (Windes et al, 1989) and the computational effort is considerably increased.…”

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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“…Our work on this topic eg. ; [43][44][45][46][47] will continue in the next funding period. There are special procedures necessary to deal with these problems.…”

Section: Ii12 Packed Bed Reactorsmentioning

confidence: 99%

(New process modeling, design and control strategies for energy efficiency, high product quality and improved productivity in the process industries)

1991

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The results of the research caIried out from June 1989 through December 1991 and supported by the Department of Energy have been reported in a series of research papers, conference presentations, short courses, and seminars. These are listed in detail in section II.4 below. Several additional papers are in preparation. In this renewal proposal, it is impossible to provide a detailed account of ali the numerous developments and results obtained during the last 21/2 years. However, we are providing separately a report including reprints and preprints of ali publications. Thus in what follows, we shall only summarize the highlights of our work to date. ti.1 RESILIENT DESIGN AND CONTROL OF CHEMICAL REACTORS

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“…Early approaches to field reconstruction in distributed process systems exploited results from dynamic linear systems theory to develop optimal state space observers through spatially discretized models of the system equations, such as finite differences or finite element methods (Alvarez et al, 1981;Harris et al, 1980;Kumar and Seinfeld, 1978;Windes et al, 1989). First, the original infinite dimensional system was approximated by a large number of ordinary differential equations describing the evolution of the relevant variables on a grid of space positions.…”

Section: Introductionmentioning

confidence: 99%

Optimal sensor placement for state reconstruction of distributed process systems

2004

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In this contribution we propose a systematic approach to field reconstruction of distributed process systems from a limited and usually reduced number of measurements. The method exploits the time scale separation property of dissipative processes and concepts derived from principal angles between subspaces, to optimally placing a given number of sensors in the spatial domain. Basic ingredients of the approach include the identification of a low-dimensional subspace capturing most of the relevant dynamic features of the distributed system, and the solution of a max-min optimization problem through a guided search technique. The low-dimensional subspace can be defined either through a spectral basis (eigenfunctions of a linear or linearized part of the operator) or through a semiempirical expansion known in the engineering literature as the ProperOrthogonal Decomposition (POD) or Karhunen-Loeve expansion. For both cases, the optimal sensor placement problem will be solved by taking advantage of the underlying algebraic structure of the low-dimensional subspace. The implications of this approach for dynamic observer design will be discussed together with examples illustrating the proposed methodology.

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Dynamic estimation of temperature and concentration profiles in a packed bed reactor

Cited by 25 publications

References 27 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

(New process modeling, design and control strategies for energy efficiency, high product quality and improved productivity in the process industries)

Optimal sensor placement for state reconstruction of distributed process systems

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