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The Application of Fuzzy Adaptive PID Theory in Deaerator
System
Zhou Nina
Department of Electronics & Elect. Eng., Baoji Univ. of Arts
& Sci., Baoji, China e-mail: [email protected]
Abstract：The oxygen in the boiler feed water is the main reason
of device corrosion. Oxygen corrosion is one of the biggest dangers
of boiler. The common deoxidization method is heating power
deoxidization. The temperature and pressure must be kept steady to
get rid of oxygen in water effectively. The deoxidization system
with a nonlinear structure is characterized by multi-input
multi-output and has great time delay. Its temperature and pressure
are strongly coupled. For these reasons, it is hard to establish
its precise mathematical model. But these requirements are almost
unreachable when the ordinary PID control scheme is applied.
Intelligent method is required. This paper presents a method of
designing based on the fuzzy adaptive PID control theory.
Simulation of control system is performed to study the performance
of fuzzy adaptive PID control by MATLAB and other control methods,
simulation results show fuzzy adaptive PID control theory reduces
settling time and also shows a very brilliant performance comparing
to other methods. It is suitable for application in engineering
projects.
Keywords: deoxidization system; temperature control; fuzzy
adaptive PID control theory 1 Introduction
The oxygen in the boiler feed water is the main reason of device
corrosion and it can destroy the water feeding system and the
boiler to go wrong. In order to decrease device’s oxygen corrosion
and ensure power devices’ safety, deoxidization system in the water
feeding must be used.
1.1 The Current Research Situation at Home and Abroad
Many scholars have put forward their own methods to solve the
problem about oxygen in water, such as: Cai Ying and Li Song-bo
proposed that normal methods to get rid of oxygen in water were
heating power deoxidization, vacuum deoxidization, chemical deoxi-
dization and analysis deoxidization [1]. Qu Yan-bin and other
people designed many dimensions fuzzy cont- roller based on fuzzy
control theory to control pres- sure and water level of deaerator
system in their papers[2]. American Ben-Abbdennour and other three
people wrote the paper on Robert Multivariable Ro- bust Control of
a Power Plant Dearator[3]. Fuzzy adaptive PID control theory is
proposed to control the temperature and pressure of the dearator in
this paper.
2 The Mathematical Model of the Dearator System and Controlling
Methods
2.1 The Mathematical Model of the Dearator System
The step signal is as the input. Through mathe- matical
operation and the experiments characteristic curve , the transfer
function can be obtained. It is 2.2 The Application of Fuzzy
Adaptive PID Control Theory in Controlling the Temperature and
Pressure of the Dearator.
se
ssG 4316.4
4.9)(
(1-1)
Remarks: The Project of Tackle Key Problems in Science and
Technology of Baoji City ,Number: 08KG02-3
Focal Project of Baoji Univ. of Arts & Sci., Number:
ZK08130
The dearator’s pressure holds on 0.02~0.025Mpa. When temperature
is about 104℃, the oxygen in water overflows, and the volume of
oxygen in water is almost zero through calculating. And if the
temperature in the dearator is below 107℃,the temperature cann't
beyond the most permission pressure. The temperature cont-
32978-1-935068-06-8 © 2009 SciRes.
Proceedings of 2009 Conference on Communication Faculty
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rolling range is 104 土 3℃ . 2.2.1 Fuzzy Adaptive PID Control
E and ec are the inputs in fuzzy adaptive PID control theory, by
using fuzzy rules to rewrite PID parameters online to meet the
requirement of setting PID parameter at different times. Inputs is
temperature deviation e and rate of change of deviation ec, outputs
is Kp,Ki,Kd that is settled by fuzzy controller, output control
amount is achieved through PID operation.
Figure 2. The Bolck Diagram of Fuzzy Adaptive PID Controller
Considering the sensor's error and the actual
application, temperature’s error e is controlled in the scope of
101 to 107 ,℃ ℃ the change of temperature’s error ec is limited
between -0.5 ℃ and +0.5 . ℃ The temperature controlling amount is
output variable and also the open degree of electromagnetic control
valve, and its scope is 0 percentage to 100 percentage.
u
2.2.2 The Establishment of Fuzzy Controller Rules Table[5]
Inputs and outputs are all presented by seven words: {negative
big, negative middle, negative small, zero, positive small,
positive middle, positive big}, the abbr. forms are {NB, NM, NS,
ZE, PS, PM, PB}.Considering form's most simple and computing
simplest, triangle subordinated function is used to stand for the
subordinated function of e ,ec, and the controlling amount.
In different e and ec , the setting request for parameter
Kp、Ki、Kd are as follows:
①When e is bigger enough, Kp should be bigger and Kd should be
smaller in order to achieve rapid responding time and to avoid the
starting e becoming bigger instantly, which may cause different
oversa- turation and make the control exceed allowance extent. At
the same time integral effect should be limited and Ki =0 should be
generally made in order to aviod bigger
overshoot because of integral oversaturation.
Table 1. Look-up Table of Ccontrol Rules
Figure 1. Normal PID Control
Figure 2. Fuzzy Control
②When e and ec are all middle, Kp,Ki,Kd
should be middle in order to make the overshoot decrease and to
guarantee the response speed.
When e is smaller, the integral is effective, Ki,Kd should rise
to make the system more stable. Meanwhile, to aviod oscillation at
settling value nearby and thinking about the system's anti-jamming
performance, Kd should be selected as follow principles: when ec is
smaller enough, Kd can be bigger and normally it is middle; when ec
is bigger enough, Kd can be smaller .
The look-up table of control rules is in Table 1.
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Proceedings of 2009 Conference on Communication Faculty
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3 The Analysis for the Simulation Results [6] Figure 3. Figure 1
is the result using normal PID control method, Figure 2, the result
of fuzzy control method, and the result of fuzzy adaptive PID
control is as Figure 3.
The simulation results are as Figure 1, Figure 2 and
4 Conclusions
Using simulink model finishing simulation, the results show
fuzzy adaptive PID control method is superior to other methods; it
has rapid response speed, high precision and simple structure,
easily changing. It can control the temperature of dearator at
104±3 nearby,℃ having engineering application value.
Figure 3. Fuzzy Adaptive PID Control Reference
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Proceedings of 2009 Conference on Communication Faculty
