Binary Distillation Column Research Articles

Development and Experimental Verification of a Time-optimal Startup Strategy for a High Purity Distillation Column

The aim of this study is the development and experimental verification of a time-optimal startup strategy for binary high purity distillation columns. Simulated annealing (SA) is chosen as the optimization tool. This direct stochastic search method offers the possibility of finding global optima.

Identification and Control of an Industrial Binary Distillation Column: A Case Study

The challenging problem of identification and control of an industrial binary distillation column is addressed in this paper. Process identification represents an alternative to modeling and is shown to be the appropriate procedure for predictive control design. The predictive controllers based on the identified model ensure stability and high performance for a wide operating range of the industrial distillation column.

Identification and Control of an Industrial Binary Distillation Column: A Case Study

The challenging problem of identification and control of an industrial binary distillation column is addressed in this paper. Process identification represents an alternative to modeling and is shown to be the appropriate procedure for predictive control design. The predictive controllers based on the identified model ensure stability and high performance for a wide operating range of the industrial distillation column.

A graphical method for designing reactive distillation columns. I. The Ponchon-Savarit method

We show how to construct a Ponchon–Savarit diagram for a binary reactive distillation column, illustrating it specifically for isomerization and decomposition reactions. We first show the properties needed for points to lie on a straight line in composition/enthalpy space. Then, for the isomerization reaction, we show how to step off the stages using a reactive cascade difference point. In the Ponchon–Savarit diagram, the reactive cascade difference point has two elements. One is the composition coordinate formed as a linear combination of stoichiometric coefficient vectors and the top product composition. The other is the enthalpy coordinate formed by combining the top product molar enthalpy, the condenser molar duty and the molar heat of reaction. Finally, and in a similar manner, we construct the Ponchon–Savarit diagram for a decomposition reaction.

Fault Detection and Isolation in the Presence of Unmeasured Disturbance: Application to Binary Distillation Columns

In this paper an exhaustive analysis is given in order to design a fault detection filter for the isolation of the pressure decay and the unmeasured feed composition in a binary distillation column. Our design scheme is based on nonlinear observers, state elimination, and the inversion of the error equation. The diagnostic model is developed from chemical principle and relations.

Graphical methods for reaction distribution in a reactive distillation column

AbstractVisual methods of determining how to distribute reaction zones within a binary reactive distillation column were studied using both the Ponchon–Savarit and McCabe–Thiele methods modified to account for the reaction. Two types of reactions are compatible with a totally binary system: isomerization and dimerization. For isomerization with a heavy reactant and a light product, both diagrams indicate the potential for a pinch point if the reaction zone is in the stripping section and no such potential if the zone is in the rectifying section. These same diagrams show that the column will have fewer stages and less usage of utility to yield the same final top and bottom products with the reaction in the rectifying section. The situation reverses if the reactant is the light species for isomerization, suggesting reaction should then take place in the stripping section. The heat effect from the isomerization reaction is considered for four cases depending on whether the reaction is endothermic or exothermic. Even if the heat of the isomerization is dominant, the results do not change: with a heavy reactant and a light product, the separation performance is better when the reaction takes place in the rectifying section. In the dimerization reaction, where two light reactants form a heavy product, the light reactant enriches as we go down the column and the composition profile is reversed in a Ponchon–Savarit diagram with the reaction in the rectifying section even if there is no pinch point. Results on the location of reaction zones are confirmed by rigorous simulations.

A Comparison of Control Strategies for Batch Distillation

The present work describes the development and experimental evaluation of a computational system used to operate a binary pilot batch distillation column based on digital control algorithms. An open system for data-acquisition is proposed in order to allow control computational codes to be easily implemented. Two Adaptive Control strategies (Programmable Adaptive Control and Self-tuning Regulator), a Fuzzy Controller and digital conventional PID controllers were implemented. A comparative study is presented based on experimental results. All developed control algorithms were easily implemented and permitted to operate the batch distillation column efficiently.

An Alternative Formulation for One-Layer Real Time Structure for Control and Optimization Based on the Inverse of the Process Gain

In this paper a new formulation for one-layer real time structure for control and optimization is presented. This new formulation is based on a constrained Quadratic Dynamic Matrix Control (QDMC) and it is applied to an ideal binary distillation column. In this formulation, at each sampling time, the values of the outputs of the process are fed into the optimization-control structure, which supplies the new values of manipulated variables. A linear dynamic model of the process is combined to a stationary model and both models are used to perform an on-line search for the best operational conditions. This alternative formulation generates a convex problem, which can be solved with less sophisticated optimization algorithms. Linear and non-linear economical objective functions are considered. Due to the non-interaction feature between the optimization and control procedures in the one-layer structure, it is not observed any oscillation problems in control variables, even when non-linear economical objective functions are used.

Adaptive Fuzzy TSK Model-Based Predictive Control Using a Carima Model Structure

A new long-range predictive control algorithm for non-linear processes is proposed and is based on the popular Generalized Predictive Control (GPC) algorithm using the Takagi-Sugeno Kang (TSK) piece-wise fuzzy modelling approach. The proposed fuzzy modelling approach is integrated with the proposed control algorithm to form an adaptive control scheme based on a Controlled Auto-Regressive Integrated Moving Average (CARIMA) model structure. The performance of the adaptive control scheme is assessed using a series of experiments on the binary distillation column and on the Continuous Stirred Tank Reactor (CSTR) system.

On the Impact of Mass and Heat Integration on Design and Control of Distillation Column Systems

The influence of mass and heat integration on design and control of three different column systems is investigated. Frequency dependent Relative Gain Analysis (RGA) is used to assess the merits of design modifications for the control loop decoupling of a binary heat-integrated distillation column. For the separation of a ternary mixture, the direct sequence and one of its heat-integrated variants are investigated. Using steady-state sensitivity analysis, it is shown that the concentration of low boiling components in the feed to the second column has a strong impact on the energy demand and controllability of column sequences. An additional loop controlling this concentration is recommended if large disturbances in feed composition are to be expected. Where necessary, the results are verified by nonlinear closed-loop simulation.

Circumventing an Azeotrope in Reactive Distillation

Using a McCabe−Thiele diagram, we explain nonintuitive behavior in a binary reactive distillation column where we react and separate two isomers displaying a maximum boiling azeotrope. Placing sufficient reaction on only two trays in the top section of the column, we shift the top operating line to lie below the 45° line. On lower nonreacting trays, we then easily step past the azeotrope. Once past the azeotrope, we even find that the column temperature decreases as we step down the column.

Minimizing Entropy Production Rate in Binary Tray Distillation

In this work we increase the second law efficiency in an ideal binary tray distillation column by allowing heat exchangers on all trays. We find by numerical optimization, the duties of the heat exchangers that give the highest second law efficiency of the column. The entropy production rate was reduced by 30-50% compared to adiabatic operation for two different columns. The numerical optimum was in agreement with the result of an Euler-Lagrange minimization in which the total entropy production rate was described by irreversible thermodynamics. The minimum was not characterized by equipartition of forces. This paper was presented at ECOS'00, Enschede, July 5-7, 2000

A nonlinear profile observer using tray temperatures for high-purity binary distillation column control

A new, concise nonlinear profile position observer using tray temperatures instead of tray compositions is proposed. Composition measurement has been one of the major difficulties associated with the composition control of distillation columns because the on-line analyzers still suffer from large measurement delays, high investment/maintenance costs and low reliability. One of common alternatives to the analyzers is to use the secondary measurement such as tray temperatures which is able to infer the tray compositions. The performance of the nonlinear control scheme which consists of this nonlinear profile observer and the model-based controller for profile position control of high-purity distillation column proposed by Han and Park (1993, A.I.Ch.E. Journal, 39(5), 787–796) has been tested and compared with that of Han (1993, Control of high-purity distillation columns using a nonlinear wave theory, Ph.D. thesis, KAIST) in simulation of high-purity distillation column. The results of this new control scheme is very similar to Han and Park (1993). The control scheme is insensitive to the noise of the temperature measurements and so simple that it can be directly applied to the real high-purity distillation columns.

Linearizing control of a binary distillation column based on a neuro-estimator

In this work, the LV-control problem in binary distillation columns is addressed. With least prior knowledge, a linear reference model with unknown terms is obtained. The time variations of the unknown terms are estimated using two on-line trained perceptrons. These estimates are subsequently used to design a feedback linearizing-like controller. The closed-loop behavior is analyzed through numerical examples. The resulting controller shows robustness against external disturbances and set-point changes.

Parametric uncertainty modeling for robust control: a link to identification

The dynamic behaviour of a non-linear process can often be approximated with a time-varying linear model. In the presented methodology the dynamics is modeled non-conservatively as parametric uncertainty in linear time invariant models. The obtained uncertainty description makes it possible to perform robustness analysis on a control system using the structured singular value. The idea behind the proposed method is to fit a rational function to the parameter variation. The parameter variation can then be expressed as a linear fractional transformation (LFT). It is discussed how the proposed method can be utilized in identification of a nominal model with uncertainty description. The method is demonstrated on a binary distillation column operating in the LV configuration. The dynamics of the column is approximated by a second order linear model, wherein the parameters vary as the operating point changes. It is shown that a diagonal PI control structure provides robust performance towards variations in feed flow rate or feed concentrations. However including both liquid and vapor flow delays robust performance specifications cannot be satisfied with this simple diagonal control structure.

Linear measurement feedback control of nonlinear plants

Abstract For multi-input multi-output (MIMO) (possibly open-loop unstable) plants we consider the problem of designing a nonlinear feedforward-feedback controller driven by on-line measurements. The proposed controller stems from a nonlinear geometric control framework, guarantees closed-loop robust exponential stability, contains a feedforward-feedback compensator of dynamic interaction, tolerates modeling errors and has a tuning procedure that amounts to the tuning of independent SISO (single-input single-output) systems. The control of an azeotropic binary distillation column with tray hydraulics dynamics is considered as an application example.

A Design methodology of a soft sensor based on local models

A soft sensor is an empirical model, which estimates variables that is infeasible to measure on-line from other correlated variables. Because constructing a soft sensor is a process of data based empirical modeling, the homogeneity in the training data set is very important. If a process experiences a wide operation range or lasting significant disturbances, the data homogeneity is damaged and frequently results in several sub-clusters, which causes the prediction power of a soft sensor to be degraded. In this paper, we proposed a modeling procedure that involves classification of training data and subclass modeling. PLS and NLPLS are adopted selectively as the subclass modeling algorithm and wavelet coefficients thresholding is used to remove noises contained in signals without severe distortion of the signals. Also, weighted X variables based on Variable Importance to Projection(VIP) through exploratory PLS are used to enhance the performance of the subclass models. The proposed methodology has been illustrated using an application to the development of a soft sensor for composition estimation of a binary distillation column simulated with HYSYS. The soft sensor based on the proposed scheme has shown better performance and robustness.

Intermediate reboiler and condenser arrangement for binary distillation columns

AbstractThe most thermodynamically efficient configuration for adding or removing heat from an intermediate location of an ideal binary distillation column distilling pure products is derived. The optimal policy requires that preconditioning of the feed be part of the overall decision‐making process. The optimal configuration can be determined through the use of two parameters, αIR and αIC, that are solely functions of feed composition. Simple and readily usable heuristics using these parameters are developed that help instantly identify the most efficient selection among (1) totally vaporizing and returning a side‐draw liquid stream from an intermediate location of the distillation column, (2) partially or totally vaporizing a portion of the given saturated liquid feed, (3) partially or totally condensing a portion of the given saturated vapor feed, and (4) totally condensing and returning a side‐draw vapor stream from an intermediate location of the distillation column.

Identification and Control of an Industrial Distillation Column: A Case Study

The challenging problem of identification and control of an industrial distillation column is addressed in this paper. It aims at presenting a process analysis, an identification procedure and a control design for a binary distillation column. Process identification, which represents an alternative to modeling is shown to be the appropriate procedure for predictive control design. The predictive controllers based on the identified model indeed ensure stability and a high performance for a wide operating range of the distillation column.

Plantwide Controller Tuning Using a Multiobjective Genetic Algorithm

Plant wide controller tuning is complicated by process recycles and the interactions between controllers. Multiple objectives exist, such as limited overshoot, rapid rise time, and the avoidance of oscillatory and unstable behavior. Tuning each controller independently based on a single objective may lead to less satisfactory performance. A genetic algorithm (GA) which uses evolutionary rules based on a ranked population of solutions is proposed to address this problem. A population of solutions is ranked based on multiple objective function values, and evolutionary rules are employed to determine optimal solutions. The algorithm provides encouraging results when tuning four PI controllers for a binary distillation column.