Computerized Water Level Control System for System Generator of Qinshan Nuclear Power Plant

Copyright © IFAC Control of Power Systems and Power Plants, Beijing, China, 1997

COMPUTERIZED WATER LEVEl;- CONTROL SYSTEM FOR SYSTEM GENERA TOR OF QINSHAN NUCLEAR POWER PLANT

Wen-peng LANG

M. Tahir KHALEEQ

Dept. a/Control Engg. shanghai

David Guosen HE

SHANGHAI

Weiqing ZHAO

UNIVERSITY

200072, P.R.CHINA

Abstract: This paper presents a computerized water level control system for Vertical U-Tube Type Steam Generator for China QINSHAN Nuclear Power Plant of Pressurized Water Reactor. It is a rule-based optimal digital controlled system with good experience of the reactor operators' long term records and experience. Copyright © 1998 IFAC Keywords : Steam Generator, Vertical U-Tube Type, Level Control System

Optimal Digital Controller

Weight Factor

Fig. 1. illustrates the design steps of the computerized

1. INTRODUCTION

control system. Details of the design steps can be This report presents a computerized water level

found in the reports and papers listed in the references.

control system for Steam Generators (SG) in PWR.

These steps are briefly discussed in this section.

The control system is a controller with the experience of the reactor operator for on-line correction of the Plant

controller parameters. For the correction of the controller parameters, weighting factors (WF) are introduced.

An optimal digital level controller has

been designed for full reactor power reactor operation Computer

and weighting using production rules. An expert system has

been

developed for

the computer

simulation. In the following sections some details of

Fig. 1. Computerized control

this work is discussed. 2. DESIGN OF CONTROL SYSTEM

155

and A, M, B, N, MT, BT, and NT are constant Non-linear

Linearization

f---+ model

Digitization

1 Acquisition of Expert's

Weighting

---.

Knowledge

matrices of appropriate dimensions.

&

Factors Calculation I

Control System Design

-

This model represents and approximated behavior of

1

-

the

SG around the equilibrium point of the

Optimal

corresponding operating range. For this system we

Controller

used sampling period, T=O.l units , and obtained following discrete form of the system mo~el:

Design I

!

X(k+ 1)=MD*X(k)+BD*U(k)+ND*D(k)

(4)

Y(k)=CD*X(k)+ED*U(k)+FD*D(k)

(5)

Development of Production rules

2.2

DESIGN

OF

DIGITAL

OPTIMAL

CONTROLLER

Fig. 2. Design steps for computer control system For design of the controller two state-space models, 2.1 LINEARlZATION AND DISCRETIZATlON

one consists of primary side parameters and another consists of secondary side parameters, are developed

A linear state space model is developed by linearizing

from the complete state-space model of the SG

the nonlinear equations using piece-wise linearization

discussed in the previous section. The state space

method and then equivalent discrete equations are

model of the secondary side of the SG is used for

obtained for appropriate sampling period. The

controller design and the state space model of the

linearized discrete model is developed to techniques.

primary side is used for calculation of the heat

A computer simulation has been carried out for the

transfer rate with taking considerations of the

SG of Qinshan Nuclear Power Plant (QNPP).

disturbances in the primary side. The heat transfer rate is used in the secondary side model. The main

dX(t)/dt=flX(t),U(t),D(t)]

reason of this approach is to get a low order

(I)

controllable system equations for design of the proposed controller.

Where X(t) is state vector, U(t) is system input, D(t) is disturbance vector . A linearized models is developed by using piecewise linear approximation

The following six order dynamic state space form of

method. The state-space form of. the linearized model

the sceondary side model is used for design of the

is following

controller. AdXldt=MX+BU +ND

(2)

X(k+ 1)=AX(k)+BU(k)+CD

(6)

Y(k)=DX(k)+EU(k)+FD

(7)

the standard form is : The optimal controller is a digital optimal PI dXldt=MT*X+BT*U +NT*D

(3)

controller with constant gain state feedback for proportional control action and dynamic output feedback for integral control action. An augmented

where

standard state-space form is developed. X=

[~Tl.1T2

~T3

.1Uo

~Vv

Mri

~Fro.1P

~W]T

U=

Z(k+ 1)=MZ(k)+NV(k)

[~Wfw],

D = [~Tpr ~Wpr

~Ppr

~Tfw

~WS]T

where

156

(8)

Me

[~ ~]

N=[B

designed in the previous section It IS necessary to design an observer which observes all the states from information of inputs (input and disturbences)

E]

and output variables. The Eq. (8) is a seven order standard state-space form As the steam and feedwater flow measurements are

of Eq. (6) and used for design of an optimal controller

too uncertain to be used at low power conditions w~

to achieve a digital PI controller using the following

can

control law:

estimate

these

input

variables

form

the

measurements of pressure P and water level Lw. V(k)=-G I [X(k+ 1)-X(k)]-G2Y(k)

(9) The observer has been designed from the actual

where, G 1 is state

feedback gain

model

vector for

using

standard

digital

observer

design

technique.

proportional control action and G2 is dynamic output feedback vector for integral control action.

2.4

ESTIMATION OF WEIGHTING FACTORS

Z(O) is calculated by using Eqs. (I) and (2) to include The weighting factors are estimated using system

the effect of step input, disturbances and initial values

parameters, dynamic behavior of the SG and

of state variables X(O) and get the control action

experience of reactor operators according to the

accordingly.

following facts : For estimation of the gain vectors Gland G2 the Degree of non-linearity in the process.

linear digital regulator design technique is adopted to

Degree of uncertainty in the measuring signals.

minimize the performance index 1.

Reactor

conditions(steady

operating

state/transient).

J = [ZT(k)QZ(k) + V\k)RV(k)]

Internal/external disturbances. Reactor power level.

where Q is a positive semidefinate matrix and R is a positive defmite matrix.

Each weighting factor is the sum of all the weighting factors associated with the facts which deviates the

If the pair (M, N) is completely controllable which is

reactor power from steady state operation. The

a necessary condition and Q is chosen so that (M, Q)

weighted sum can be described by

is observable, the closed-loop system will be asymptotically stable. The matrices Q and R can be

N

chosen so that the eigenvalues of the closed loop

WF(P)=

system are located in a desired region of the complex

IWi

(10)

i=l

plane to achieve desirable degree of stability and where, Wi are corresponding weighting .factors of N

system damping.

number of facts which effect on steady state operation. Wi are calculated using the knowledge of the

2.3 DESIGN OF OBSERVER

experienced reactor operator. The weighted sum WF All the state variables are not measurable except the

is function of reactor power. Threshold value I is

pressure P which is measurable with existing physical

assigned to the weighted sum for steady state

sensors. All the input variables have physical sensors

operation within a particular range of reactor

and are measurable. Therefor, for implementation of

operation.

the state-feedback digital optimal controller which is

157

For estimation of the weighted sum WF of the

action.

weighting factors Wi we can defme the weighted sum as the ratio of the controller parameter of particular

The number of rules for each above mentioned

linear range with steady-state reactor operation CPs to

category depends union:

the controller parameter estimated with considering all the facts discussed above CPa as :

the number of operating linear ranges form startup to full power,

CPs WF(p)= - CPa

the number of facts as consider as possible and

(11)

the type of actions including regulation, trip, alarm, etc.

A set of weighted sum should be estimated off-line for every range of reactor operation for which the

The metarules for nine linear ranges of the reactor

linearized

power can be developed as following.

models

are

developed.

Repeated

simulations have to be performed to obtain an accurate weighting sum and to achieve a set of desired

IF P<= 10 AND P>=O

closed-loop eigenspectrum.

THEN call DEC-l AND call RB-l IF P<= 25 AND P>= I 0

All the possible facts should be considered during

THEN call DEC-2 AND call RB-2

calculation of the weighting factors . Accuracy of the

IF P<=35 AND P>=25

weighting factor is important which effects on the

THEN call DEC-3 AND call RB-3

overshoot,

IF P<=50 AND P>=35

oscillation

and

steady-state

error

characteristics of the controller.

THEN call DEC -4 AND call RB-4 IF P<=60 AND P>=50

2.5

DEVELOPMENT OF THE RULE BASE

THEN call DEC-5 AND call RB-5 IF P<=70 AND P>=60

In the rule-base the knowledge is coded in production

THEN call DEC-6 AND call RB-6

IF-THEN rules. Each operating range corresponding

IF P<=80 AND P>=70

to a linearized model has a particular set of rules.

THEN call DEC-7 AND call RB-7

Metarules are incorporated for proper selection of a

IF P<=95 AND P>=80

set of rules according to the reactor power level.

THEN call DEC-8 AND call RB-8

Heuristic search strategy is adopted for selecting a

IF P<= 11 0 AND P>=90

particular set

of rules

and

determination

of

THEN call DEC-9 AND call RB-9

appropriate controller parameters. Where P is the %age of full reactor power, DEC- and The rule-base has to be developed using IF-THEN

RB- are subroutines for the corresponding power

rules as to be executed in the following mainer:

range. The subroutines DEC- are subroutines of data . base

cotaine controller parameters, set points,

find particular set of rules according to the

observer data, and other parameters for on-line

reactor power level,

calculations. The subroutines RB- are subroutines of

fmd operating conditions (steady-state, transient

rlue-base contain particular set of rule of the power

or accident) from the input parameters,

range.

fmd particular set of rules according to the In a subroutine RB-rules can be developed as :

operating conditions, find weighting factors for correction of the controller parameters,

IF P2=Pl

find appropriate controller parameters as an

THEN select RL-l

158

( steady state operation)

IF P2=PI

(transient conditions)

THEN select RL-2

Inference engine

etc.

The function of the inference engine is to decide which set of rules has to select and execute the control

The RL-are set of rules for particular conditions. The

action.

RL-I set of rules contains the steady state controller parameters. The RL-2 set of rules calculate the

Interface

deviation of power from steady state operation, select the weighting factors and correct the controller

User interface can provided for user convenience

parameters. The RL-2 contains much informations

control process can be monitored. Rule base can be

about rector operating conditions .and actions. The

modified.

RL-2 can be developed as : 3. CONPUTER SIMULATION IF P2 =PI (calculation of deviation)

THEN call CAL

A computerized control system has been developed

IF DEV =X

for Qinshan Nuclear Power Plant by using the design

THEN select RL-3

techniques discussed in previous sections.

etc.

4. CONCLUSION

The RL-3 set of rules contains the appropriate

Due to the knowledge of the experienced reactor

weighting

controller

operator and unavailability of the standard plant data

parameters which are called in subroutine DEC-.

for other power ranges the control system has been

DEV is deviation from steady-state.

varified only for full power operating range and under

factors

and

correct

the

some transient conditions. However during design stages it was taking under considerations that the

2.6 DESIGN OF CONTROL SYSTEM

control system should be successfully operate under From the discussion in the previous section. We can

all condition from startup to full power.

design a complete control system which contains the following main components: a global data base; a rule

All possible facts should be considered during

base; and inference engine; and an user interface.

calculation of the weighting factors . Accuracy of the weighting factor is important which effects on the

Global data base

overshoot,

oscilation

and

steady-state

error

characteristics of the controller. The data base contains controller parameters for different power ranges, weighting factors, measured

The proposed computerized control system takes the

values of input, output and disturbances and alarm set

advantages of both conventional control techniques

points.

and the knowledge of the experienced reactor operators. Total dependency on the I?Jathematical model, reactor operator and sensors are eliminated

Rule base

specially at low power reactor operation and during Function of the rule base is to provide knowledge

transient conditions.

sources to the inference engine of the control system. The knowledge is coded in production rules. Each

Proper designing of the proposed controller can

operating range has a particular set of rules.

improve the functioning of the control system and

159

accuracy of the control action, and reduces the

Patterson, " Introduction to Artificial Intelligence & Expert Systems. Prentice Hall, New Jersey, 1990.

execution time.

Levine, et aI., "A comprehensive Guide to AI and Expect Systems, ": McGraw-HiIl, Inc., 1986. Glorioso, F. C. C. Osorio, " Engineering Intelligent

REFERENCES

Systems: Concepts, Theory, and Applications, Tahir Khaleep, "PWR Steam Generator Transient

" Digital Equipment Corporation, USA, 1980.

Analysis and Computerized Water Level Control System ,"Project Report, Shanghai P.R China, April 1994. Tahir

Khaleeq,

Linearized

Digital

Mathenatical Model and Design of an Optimal Linear Digital Regulator for Steam Generator of Qinshan Nuclear Power Plant, "Research Report #8, Jun. 1995. Tahir

Khaleeq, "Observer

Based

Digital

Optimal Controller for Water Level Control of Steam Generator of Qinshan Nuclear Power Plant, Research Report #9, October 1995. Tahir Khaleeq, Wen-peng Lang and David G.He, "Rule-Based Real-Time Control System for PWR Steam Generator Water Level Control, "Proc. IFAC Youth Automation Conference (IFAC YAC'95), Beijing P. R. China, August 22-25,1995. Tahir Khaleeq, Wen-peng Lang and David G .He, "Application of Artificial Intelligence in the Steam Generator Water Level Control in Nuclear Power Plants, "IFAC Symposium on Control of Power Plants and Power Systems, Maxico, Dec. 1995. Tahir Khaleeq, Wen-peng Lang and David G. He, "Digital Optimal Level Controller for Steam Generator

In

Pressurized

Water

Reactors,

" Chinese Journal, Shanghai, 1995, (submitted in Chinese). Tahir Khaleeq, Wen-peng Lang and David G. He, "CAD Facility for Design a Control System for Water Level Control of Steam Generator in PWR, " Chinese Journal, Bei jing, 1995, (submitted in Chinese). Lang Wen-peng, He David Guo-Sen, "Optimal Design of Process Measurement & Control Instrumentation & Systems, " Doctor Course Lecture Text, Shanghai University, P. R. China, 1993.

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