Dynamic modeling and validation of 2-ethyl-hexenal hydrogenation process

Both, Roxana; Cormoş, Ana-Maria; Agachi, Paul Şerban; Festila, C.

doi:10.1016/j.compchemeng.2012.11.012

Cited by 14 publications

(12 citation statements)

References 15 publications

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“…The hydrogenation process is complex, characterized by nonlinear and distributed behavior. The first approach, presented in [5],was to use a simple model of the process, validated by plant data, which describes its most important properties in combination with an advanced control algorithm which takes into account the model uncertainties, the disturbances and control signal limitations, robust control. The results were satisfactory, the desired performances being met.…”

Section: Process Descriptionmentioning

confidence: 99%

Active disturbance rejection controller for chemical reactor

Both¹,

Dulf²,

Muresan

2015

AIP Conference Proceedings

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Articles you may be interested inA mathematical treatment of the use of ultrasound in a catalytic reactor with controlled activity profile AIP Conf.Active structural acoustic control of radiation due to broadband disturbances Abstract. In the petrochemical industry, the synthesis of 2 ethyl-hexanol-oxo-alcohols (plasticizers alcohol) is of high importance, being achieved through hydrogenation of 2 ethyl-hexenal inside catalytic trickle bed three-phase reactors. For this type of processes the use of advanced control strategies is suitable due to their nonlinear behavior and extreme sensitivity to load changes and other disturbances. Due to the complexity of the mathematical model an approach was to use a simple linear model of the process in combination with an advanced control algorithm which takes into account the model uncertainties, the disturbances and command signal limitations like robust control. However the resulting controller is complex, involving cost effective hardware. This paper proposes a simple integer-order control scheme using a linear model of the process, based on active disturbance rejection method. By treating the model dynamics as a common disturbance and actively rejecting it, active disturbance rejection control (ADRC) can achieve the desired response. Simulation results are provided to demonstrate the effectiveness of the proposed method.

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Section: Process Descriptionmentioning

confidence: 99%

Active disturbance rejection controller for chemical reactor

Both¹,

Dulf²,

Muresan

2015

AIP Conference Proceedings

Self Cite

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“…The developed model (Both, 2013), consisting of numerous partial differential equations and several algebraic ones, was implemented and validated using plant data acquired courtesy of S.C. Oltchim S.A. This model is useful in the design, optimization and operation of the chemical reactor and especially in control design and testing.…”

Section: Mathematical Models Distributed Parameter Nonlinear Mathematmentioning

confidence: 99%

“…Motivated by these reasons, in previous works (Both, 2013), a first principle based mathematical model was developed starting only from some equations describing the hydrogenation reaction kinetics. The developed model (Both, 2013), consisting of numerous partial differential equations and several algebraic ones, was implemented and validated using plant data acquired courtesy of S.C. Oltchim S.A.…”

Section: Mathematical Models Distributed Parameter Nonlinear Mathematmentioning

confidence: 99%

“…The equations describing the nonlinear mathematical model used are (Both, 2013):  The total mass balances for the gas and liquid phases are (Both, 2013…”

Section: Mathematical Models Distributed Parameter Nonlinear Mathematmentioning

confidence: 99%

“…The linear operational mathematical model was determined using experimental identification methods based on plant data, as a transfer function matrix of second order elements between the main input and output variables (Both, 2012): the 2-ethyl-hexanol recirculated flow (Qoct), the input temperature of the reactants (Tin), the output temperature of the product (Tout) and the output concentration of the product (Cout). …”

Section: Operational Mathematical Modelmentioning

confidence: 99%

See 2 more Smart Citations

Advanced Control of a Complex Chemical Process

Both

Dulf

Cormoş

2016

Braz. J. Chem. Eng.

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-Three phase catalytic hydrogenation reactors are important reactors with complex behavior due to the interaction among gas, solid and liquid phases with the kinetic, mass and heat transfer mechanisms. A nonlinear distributed parameter model was developed based on mass and energy conservation principles. It consists of balance equations for the gas and liquid phases, so that a system of partial differential equations is generated. Because detailed nonlinear mathematical models are not suitable for use in controller design, a simple linear mathematical model of the process, which describes its most important properties, was determined. Both developed mathematical models were validated using plant data. The control strategies proposed in this paper are a multivariable Smith Predictor PID controller and multivariable Smith Predictor structure in which the primary controllers are derived based on Internal Model Control. Set-point tracking and disturbance rejection tests are presented for both methods based on scenarios implemented in Matlab/SIMULINK.

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