Modelling and control of a flash evaporator through ODE system representation in PDEs form

Nguyen, Philipp; Tenno, Robert

doi:10.1109/icca.2016.7505296

Cited by 3 publications

(1 citation statement)

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“…DPS examples range from heating and cooling systems [1,2], fluid heat exchangers [3,4], biochemical reactors and similar processes [5][6][7][8], mechanical systems [9][10][11], resource recovery applications (such as under ground oil and water and coal reservoirs) [12,13] to the prediction and control of atmospheric pollution [14], epidemiological modeling [15,16] for the study of infectious diseases spread and the control of forest and meadow fires [17]. The time and space dependence makes the analysis of systems modeled by PDEs more complex than in the lumped-parameter case also depending on the type of boundary conditions.…”

Section: Introductionmentioning

confidence: 99%

A Concise Review of State Estimation Techniques for Partial Differential Equation Systems

2021

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While state estimation techniques are routinely applied to systems represented by ordinary differential equation (ODE) models, it remains a challenging task to design an observer for a distributed parameter system described by partial differential equations (PDEs). Indeed, PDE systems present a number of unique challenges related to the space-time dependence of the states, and well-established methods for ODE systems do not translate directly. However, the steady progresses in computational power allows executing increasingly sophisticated algorithms, and the field of state estimation for PDE systems has received revived interest in the last decades, also from a theoretical point of view. This paper provides a concise overview of some of the available methods for the design of state observers, or software sensors, for linear and semilinear PDE systems based on both early and late lumping approaches.

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