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ANFIS based Control Scheme for Binary Distillation Column

  • Amit Kumar Singh EMAIL logo , Barjeev Tyagi und Vishal Kumar
Veröffentlicht/Copyright: 3. Dezember 2016
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Abstract

In distillation process, composition control is very important. A continuous column has to be operated as precisely as possible to meet the purity specifications. In this work, ANFIS controllers are designed to control the methanol composition in BDC. The controller controls the methanol composition in BDC by the variation of reflux flow-rate and reboiler heat duty. Two separate ANFIS controllers namely: ANFIS A and ANFIS B are designed for the reflux flow-rate and the reboiler heat duty respectively. Each ANFIS controller has three inputs. The performance of this ANFIS control scheme is compared with NN-IMC control scheme on the basis of considered performance indicators (rise time, settling time, MSE). Performance of the ANFIS control scheme is evaluated for reference tracking and disturbance rejection cases. A perturbation of +10 % is incorporated in feed flow-rate for disturbance rejection case. In case of reference tracking, the obtained result shows that there is an improvement of 7 % in the settling time whereas, 14 % improvement in MSE with ANFIS scheme as compared to NN-IMC scheme. In case of disturbance rejection, the obtained result shows that there is an improvement of 14 % in the rise time, 41 % improvement in settling time whereas, 7 % improvement in MSE with ANFIS scheme as compared to NN-IMC scheme.

References

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APPENDIX

To develop the equation based model, the following information has been taken directly from the existing experimental setup of binary distillation column:

  1. Liquid composition on each tray

  2. Liquid flow rates from each tray

  3. Temperature of each tray

  4. Condenser and reboiler duties

To simplify the model, the following assumptions have been considered:

  1. The relative volatility α is constant throughout the column.

  2. The vapor – liquid equilibrium relationship can be expressed by

y=αx1+(α1)x

Where

α = Relative volatility

x= Composition of more volatile component in liquid, mole fraction,

y= Composition of more volatile component in vapor, mole fraction

  1. The overhead vapour is partially condensed in the condenser.

  2. The holdup of vapour is negligible throughout the system(i. e., the same immediate vapour response, dV1 = dV2 = … = dVN+1 = dV), where N= total number of trays

  3. The molar flow rates of the vapour and liquid through the stripping and rectifying sections are constant:

V1 = V2 = … = VN+1;

L2=L3= ….=LN+2

  1. Reboiler and condenser are also considered as a tray. Numbering of trays is done from the bottom i. e. boiler is considered as a first tray and condenser is considered as a last tray. This means that if there is N number of trays then boiler is first tray and condenser is (N+1)th tray.

Distillation column is divided into three different sections for the modeling point of view as shown in Figure 14. Ist section is reboiler section, IInd section is Tray section, and IIIrd section is condenser section. The material and enthalpy balance equations are obtained by applying conservation laws to these sections.

Figure 14: Distillation column used in modelling.
Figure 14:

Distillation column used in modelling.

Ist Section (Reboiler Section)

Component material balance equations

The constant molar holdup in reboiler has been considered i. e. dMB/dt=0, so by this

B=L1-VB

Component material balance around reboiler is given by

(21)MBdxBjdt=L1x1,jVByB,jL1VBxB,j

Where

MB= Liquid molar hold up in reboiler, kmoles,

L1= Total liquid flow rate from tray-1 entering to reboiler, kmole/h,

xB,j = Liquid fraction of component j in bottom product,% mole fractions,

VB = Total vapor flow rate leaving reboiler, kmole/h,

yB,j = Vapor fraction of component j in bottom product,% mole fractions,

B = Total bottom product rate, kmole/h,

The vapor fraction of component j from reboiler is given by

(22)yB,j=μ1,jvk1,jxB,j

Where

η1,jv= vaporization efficiency of component j in reboiler,

k1,j = Equilibrium constant of component j in reboiler

Total enthalpy balance equations

Total enthalpy balance equation for reboiler is given by

(23)MB.dhBdt=L1h1VBHBL1VBhB+QB

Where

h1 = Total molar enthalpy of liquid entering from tray-1 to reboiler, kJ/kmole,

hB = Total molar enthalpy of liquid leaving reboiler, kJ/kmole,

HB = Total molar enthalpy of vapor leaving reboiler, kJ/kmole,

QB = Reboiler heat duty, kW

IInd Section (Tray Section)

In the second section modelling for general i-th tray is considered. Material balance and energy balance equations is obtained for this section.

Component material balance equations

Component material balance equation for ith tray is given by

(24)dMixijdt=Li+1xi+1,jLixijViyij+Vi1yi1,j+FixFij

yij is calculated as

(25)yijnijyijyi1,j+yi1,j

Where

Mi= Molar liquid hold up on tray I, kmole

xij = Liquid fraction of component j, leaving the tray i, % mole fraction

Li = Total liquid flow rate leaving tray-i, kmole/h

Vi = Total vapor flow rate leaving tray-i, kmole/h

Fi = Total feed flow rate injected to tray-i, kmole/h

xFij = Liquid fraction of component j in feed on tray i,% mole fractions,

yij = vapor fraction of component j leaving the tray i,% mole fractions,

ƞij = Murphree stage efficiency based on vapor phase of component j on tray i

yij* = Equilibrium vapor fraction of component j on tray i

Li is an additional variable and it is related to Mi through

(26)Li=3.33lwMi/Anet.MDihw36002.204MDi

Where

lw = Length of the weir, ft

Anet = Net area of the tray, ft2

hw = Height of the weir, ft

MDi = Average molar density of liquid on tray I, kmole/ft3

Total material balance equation for ith general tray is calculated as

(27)dMidt=Li+1LiVi+Vi1+Fi

Where

Li+1 = Total liquid flow rate entering to tray i, kmole/h,

Vi–1 = Total vapor flow rate entering to tray i, kmole/h,

Fi = Total feed flow rate injected on tray i, kmole/h

Enthalpy balance equation for general tray i

Enthalpy balance equation for general tray i is given as

(28)dMihidt=Li+1hi+1LihiViHi+Vi1Hi1+FihFi

Where

hi = Total molar enthalpy of liquid leaving tray I, kJ/kmole,

Hi = Total molar enthalpy of vapor leaving tray I, kJ/kmole

Enthalpy on any tray are calculated by mixing rule as given by

(29)hi=j=1NChlijxxj
(30)Hi=j=1NCHvijyij

Where

hlij = Pure component enthalpy of component j in liquid, kJ/kmole,

Hvij = Pure component enthalpy of component j in liquid, kJ/kmole

Next section i. e. IIIrd section produces the modeling of condenser.

IIIrd Section (Condenser Section)

Component material balance equations

Reflux drum level is considered constant. This means at any time D=VNT-R.

Component material balance around condenser is given by

(31)MDdxD,jdt=VNTyNT,jVNTxD,j

Where

MD= Liquid molar hold up in the reflux drum, kmole,

D = Distillate flow rate, kmole/h,

xD,j = Liquid fraction of component j in reflux drum, % mole fractions

yNT,j = Vapor fraction of component j leaving tray NT,% mole fractions,

R = Total liquid flow rate entering to the tray NT from reflux drum, kmole/h,

VNT = Total vapor flow rate leaving the tray NT, kmole/h,

Enthalpy balance equation

The enthalpy balance equation for liquid and vapor for condenser is

(32)MDdhDdt=VNTHNTVNThDQc

Where

hD = Total molar enthalpy of liquid leaving the reflux drum, kJ/kmole,

HNT = Total molar enthalpy of vapor leaving the last tray NT, kJ/kmole,

QC = Condenser duty, kW

Simulation Algorithm

All the above equations have been utilized to simulate the model. The flow diagram of the simulation algorithm to develop the equation based model of binary distillation column is given in Figure 15. To simulate open loop binary distillation column the environment of MATLAB®/SIMULINK® is used.

Figure 15: Simulation algorithm.
Figure 15:

Simulation algorithm.

As mention in step 3, all the differential equations are solved by ode15 s, which is a variable-order multi step solver, based on the numerical differentiation formulas (NDFs). Optionally it uses the backward differentiation formulas, BDFs, (also known as Gear’s method). It works efficiently when the problem is suspected to be stiff.

Received: 2016-2-5
Revised: 2016-7-11
Accepted: 2016-7-11
Published Online: 2016-12-3
Published in Print: 2017-3-1

©2017 by De Gruyter

Heruntergeladen am 30.11.2025 von https://www.degruyterbrill.com/document/doi/10.1515/cppm-2016-0008/pdf?lang=de
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