10 11648 J Acis 20140201 11 PDF
10 11648 J Acis 20140201 11 PDF
10 11648 J Acis 20140201 11 PDF
Email address:
nee2k8@gmail.com (N. Srivastava), dktanti@yahoo.com (D. K. Tanti), akram14407@gmail.com (Md A. Ahmad)
Abstract: Heat exchanger system is widely used in chemical plants because it can sustain wide range of temperature and
pressure. The main purpose of a heat exchanger system is to transfer heat from a hot fluid to a cooler fluid, so temperature
control of outlet fluid is of prime importance. To control the temperature of outlet fluid of the heat exchanger system a
conventional PID controller can be used. Due to inherent disadvantages of conventional control techniques, Fuzzy logic
controller is employed to control the temperature of outlet fluid of the heat exchanger system. The designed controller
regulates the temperature of the outgoing fluid to a desired set point in the shortest possible time irrespective of load and
process disturbances, equipment saturation and nonlinearity.
Keywords: PID Controller, FLC, Heat Exchanger
gain 3 /
Control valve capacity for steam 1.6 /
Time constant of control valve 3
The range of temperature sensor 50 150
Time constant of temperature sensor 10
From the experimental data, transfer functions and the
gains are obtained as below.
Transfer function of process
Gain of valve 0.13
.
Transfer function of valve
Gain of current to pressure converter 0.75
Transfer function of disturbance variables
Fig 1. Shell and tube heat exchanger system control scheme. (i) Flow (dominant). (ii) Temperature
.
Transfer function of thermocouple
2.1. Assumptions
In this section the heat exchanger system, actuator, valve, 3.1. Tuning of PID Controller
sensor are mathematically modeled using the available
experimental data. The experimental process data’s are Ziegler and Nichols proposed rules for determining
summarized below[2]. values of ! , +1 234 +( based on the transient response
Exchanger response to the steam flow gain 50 / / characteristics of a given plant. Closed loop oscillation
based PID tuning method is a popular method of tuning
Time constants 30 PID controller. In this kind of tuning method, a critical gain
Exchanger response to variation of process fluid flow gain 5 is induced in the forward path of the control system. The
1 / / high value of the gain takes the system to the verge of
Exchanger response to variation of process temperature instability. It creates oscillation and from the oscillations,
Automation, Control and Intelligent Systems 2014,
2014 2(1): 1-5 3
the value of frequency and time are calculated. Table 1 Table 2. Linguistic variables.
variables
gives experimental tuning rules based on closed loop Very big
oscillation method[3,4]. VBN PS Small positive
negative
Medium
Table 1. Closed loop oscillation based
ed tuning methods.
methods NB Big negative PM
positive
Type of Controller 67 BC BD NM
Medium
PB Big positive
negative
P 0.5K 9 ∞ 0
Very big
PI 0.45K 9 0..83T 0 NS Small negative VBP
positive
PID 0.6K 9 0
0.5T 0.125T
Z Zero
The characteristic equation 1 # - F 0 in this
Table 3. Rule base for fuzzy logic controller.
controller
case is obtained as below
GH
900 # 420 =
# 43 # 0.78
78 5 #1 0 (3) ∆G
VB
NB NM NS Z PS PM PB
VB
N P
I
Applying Routh stability criterion in above eq gives VB VB VB VB VB VB
5 24.44 N N N N N N
NB NM NS Z
Control System
Maximum Overshoot
(%)
Settling Time (sec) References
Feedback PID [1] Anton Sodja et.al, "Some Aspects of Modeling of Tube-and-
47.2 88
Controller Shell Heat-Exchangers," in Proc of 7th Modelica Corif-,
FLC 0 65 Italy, pp. 716-721, Sep 2009.
[2] Subhransu Padhee, Yuvraj Bhushan Khare, Yaduvir Singh
“Internal Model Based PID Control of Shell and Tube Heat
Nomenclature Exchanger System,” IEEE, JAN 2011.
[3] Katsuhiko Ogata, “Modern Control Engineering”. 5th
RS Proportional gain
edition 2010.
TU Integral time
[4] Kiam Heong Ang, Gregory Chong and Yun Li, "PID Control
TV Derivative time System Analysis, Design, and Technology," IEEE Trans.,
Control Syst. Technol., vol. 13, no. 4, pp. 559-576, Ju12005.
RW Critical gain
[5] Mridul Pandey, K. Ramkumar & V. Alagesan “Design of
T Time period of oscillation Fuzzy Logic Controller for a Cross Flow Shell and Tube
X Angular frequency of oscillation
Heat-Exchanger,” IEEE, Mar 2012
YW Z Controller transfer function [6] Zadeh L.A., Fuzzy relation Equations and Applications to
Knowledge Engineering, Kluwer Academic Publishers,
G Error between desired output and actual output Holland, 1989
∆G Rate of error [7] Larsen P.M., Industrial application of Fuzzy Logic Control,
academic press, inc., may, 1979.
[8] BS Manke, “Linear Control System”. 9th edition 2010
[9] Fuzzy Logic Toolbox Help file in MATLAB version 7.11