Nonlinear control of a reactive distillation column

Grüner, Stefan; Mohl, K. D.; Kienle, Achim; Gilles, E. D.; Fernholz, G.; Friedrich, Matthias

doi:10.1016/s0967-0661(02)00211-3

Cited by 53 publications

(36 citation statements)

References 14 publications

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“…Gruner et al [21] proposed a non-linear control scheme for an industrial reactive distillation column operated investigated model gain scheduling for an ETBE reactive distillation column [22]. The methodology employed in this work relies on a systematic mixed-integer dynamic optimization (MIDO) framework exploring simultaneously the interactions between process and control system design [23].…”

Section: 3control Of Ethyl Acetate Rd Systemmentioning

confidence: 99%

A review: control of reactive divided wall distillation column

Meena¹,

Dohare²,

Singh³

et al. 2016

IJATEE

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Section: 3control Of Ethyl Acetate Rd Systemmentioning

confidence: 99%

A review: control of reactive divided wall distillation column

Meena¹,

Dohare²,

Singh³

et al. 2016

IJATEE

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“…Substitution of (2) into (3) and (4) leads to the time derivatives of composition and enthalpy (5,6).…”

Section: Dynamic Model For Continuous Distillationmentioning

confidence: 99%

“…For example, feed streams can be subjected to important variations in flow, composition or energy state. Therefore, to control the top and bottom compositions of a distillation column can be a difficult task due to the presence of control-loop interactions and nonlinearities [6].…”

Section: Introductionmentioning

confidence: 99%

“…The most common of the advanced approaches is the use of nonlinear multivariable models. However, the nonlinear models tend to become rigorous and computationally intensive as the process behavior becomes more complex [6]. Other approaches, like control based in neural networks, have interesting properties, like generality of model structure, capacity of learning from experimental data and expressing the process non-linearities and calculation speed [5].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Modelling and control of a continuous distillation tower through fuzzy techniques

Barceló-Rico

Gozálvez-Zafrilla

Díez

et al. 2011

Chemical Engineering Research and Design

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This paper presents a methodology for the design of a fuzzy controller applicable to continuous processes based on local fuzzy models and velocity linearizations. It has been applied to the implementation of a fuzzy controller for a continuous distillation tower. Continuous distillation towers can be subjected to variations in feed characteristics that cause loss of product quality or excessive energy consumption. Therefore, the use of a fuzzy controller is interesting to control process performance.A dynamic model for continuous distillation was implemented and used to obtain data to develop the fuzzy controller at different operating points. The fuzzy controller was built by integration of linear controllers obtained for each linearization of the system. Simulation of the model with controller was used to validate the controller effectiveness under different scenarios.The results showed that the fuzzy controller was able to keep the target output in the desired range for different inputs disturbances, changing smoothly from a predefined target output to another. The developed techniques are applicable to more complex distillation systems including more operating variables.

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“…Despite these advantages of profile control, only the endpoint property is commonly controlled in large-scale distributed parameter systems. For example, control of bottom and top product compositions in a distillation column [1,2] as well as endpoint Kappa number control in a continuous pulp digester [3,4] have been reported in the literature. An obvious advantage of the endpoint property control is that we typically have an online or laboratory measurement of the property of interest at the exit and this facilitates its implementation.…”

Section: Introductionmentioning

confidence: 99%