COMO: A Modula-2 Program for Real-Time Control of a Raw Material Mill

Copyright © IFAC Software for Computer Control. Graz. Austria 1986

COMO: A MODULA-2 PROGRAM FOR REAL-TIME CONTROL OF A RAW MATERIAL MILL P. Albertos*, F. Morant*,

J.

A. de la Puente** and A. Crespo**

*Dpto Ingenieria de Sistemas, Computadores y AutoTlUitica **Dpto Sistemas InforTlUiticos y Computaci6n Universidad Politecnica de Valencio, Valencio, Spain

Abstract. A computer program for real-time computer control of a mill process in a cement plant is described. The purpose of the process is to blend and mill r·aw materials in adequate proportions so that slurry, the resulting product, has the reqUired composition . The program has been developed from a formal specification, using an object-based methodology and the Modula - 2 programming language. The complete system consists of a st.ructured collection of tasks and monitors. Simulation and preliminary plant result s are presented. Keywords. Computer control; cement industry; computer programming; progranuoing languages; Modula-2; adaptive control

INTRODUCTION

PROCESS DESCRIPTION

In this paper, the design and implementation of a real-time process control program written in Modula-2 language is presented . The process to be controlled is a raw materials mill in a cement plant . The resulting product, named slurry, is obtained from four different raw materials with variable composition. The purpose of the control system is to keep the slurry composition as close as possible to a reference .

The raw material blending process has been largely studied and many authors have proposed solutions to the related control problem. One of the main reqUirements in the cement production is the obtention of a good slurry composition to feed the kiln from raw materials whose composition is not we 11 known and cannot be mesured continuously . A simplified scheme of the blending plant is shown in figure 1.

The control system is based on a central microcomputer connected by a serial link to an X-Ray analyzer in order to get measurements of the slurry composition. There is also a secondary microcomputer where actuator control is performed .

The raw materials involved in cement production are selected based on their chemical composition. Lime, clay, sand and pyrite are normally used . Lime and clay composition are strongly varying, but primary mixing beds tend to reduce the variance of these compositions at the mill input . The weighting of these materials is computed from both the desired slurry composition and the chemical raw materia}s composition. The cyclone separator introduces dry air into the mill so mixing is carried out and extracted in the static separator . Also external separators allow to get the grounded materials with a prescribed fineness, feeding the homogeneization silos and feeding back into mill the gross materials, which are mixed with the new one from the feeders .

The operator interface provides facilities for defining the operating conditions, such as slurry composition references,and the initial estimates of the raw material compositions. An object based methodology has been used in the program design phase. The main design aspects of the program are presented in detail and some considerations about implementation language related. Automatic control is based on an adaptive algorithm whose main features and computational aspects are also described .

The slurry chemical composition is analysed by an X-ray analyser requiring a long delay between the sample acquisition time and the time when oxide compositions are avaible.

This program is fully operational on an industrial cement plant . Finally some results and conclusions are discussed.

SCC-B

101

P. Albertos, F. Morant,

102

J.

A. de la Puente and A. Crespo

SenArntor

R-X

CONTROL SYSTEM REQUIREMENTS

'by An81ysi 5

ot an X-ray analys~r. ll:';m,lly I equire ·=.om~2 wi ch , i Tt the prototype prepru<:!-=ss.i.ng sy:3t:~m b(~i!l~: cCJn::=-.tder .:.2'<..i, 1:3 pertormed OIl TIt').,]e

JU.:,> ctl1S

datd

COJoputer. The analyser analy:::;is data. to t.h8 c-ur,trul syste m by means of an async:llronous serial link in a predefined dedi,::..ated

Th(~

function of the control sy::;t~ eID is to adju s)t the i.nput rate of raw ITl3.terials loa.in

into the co mposition

mill

:31 urry the re feren ce , To do tl1is, rn~asurernen t. :3 of the :sltlrr"y \:ornposition dre available dt the mill output.. As slurry mj 1J i [l8" i'3 d batch process, the p:3 'tirr0ted avelage C,:;l.n

so

be

that

c: lO:3e

l~ept

to

compo::;ition of the silo contl;:>ns is the a,1:;tual controll€!d v.3.ridble. MeaSlJ.rem8nt:5 of the raw rrtitte .rial'3 t"~·ompo:=.ition I.,::'an .3.1::':;0 be madl-": in or -der to improve the '.::ontrcl

("o'Illputer

tr.:-tn:~mit:3

forma.t.

The

r: ontrol

sY·3tem

a

1.:50

pL~nt

the

prc)vide

oper.,t1: or . following

:-::-.e rial

function~:3:

link,

actuator

DE'3:fine

reference

composition

and

quantity for a s lurry batch. -

Input raw mat.erials 'oomposition data.

-

Start and stop mill operation.

must

decode

the raw t.he help of d lOI:dl controll .~r. In the prototype syst~=m, the loc·a.l con troller (:.ommu nicat,es wi th the cor,t.rol syst.ems by means of a ma"t.eri.:tls weigth

The control operating support for the This includes. at least,

system

Raw materials ·:omposi t ion manually i:=. t .he Dperator as its entered l.ly d("::,ter mina t .i on involve:;; :=-ome manual analysis process. The

function.

,.:,.ontrol

tl)is input ,~nd select the required slurry c' umposition data.

adjusts

::;ettiug::s with

The cont rol

systems sends

set

points to the local c.ont:rIJlls l-, Brld receives actual actuators setting values from it.

The operator

- Get plant.

information about the state of the This should inc'lude warning

messages

(e.g.

in ca'3e

lack

of

of abnor.rn.::t l

slurry

ca n input c'ommands at any standard CRT terminal. Command syntax is shown in table 1. time by means of a

candi tions

composition

measurement::; or hatch quanti ly reieren'::e surpassed>, as well as period report on the operating conditions including variable values.

Switch between automatic and manual operation modes. For operator's convenience. a distinction betwen measur ement acquisition and actuator setting is made. When either function is in manual mode the related data (output slurry composition and actuatot percent rates) can be input by hand by tILe plant operator.

TABLE 1 Syntax of

operator commands

:: ==

define start batch stop_batch examine. total rate analysis weigths standard batch_quantity .

Process interface Composition

measurements

are

tipically

manual

automatic.

COMO: A Modula-2 Program Output to the operator includes:

1 ) Lime standard

- Warning and error messages . LS Periodic reports operating conditions.

about

the

103

plant

100 CaD -------------------- - ---- -- 2 . 8 Si02+1. 1 A1203+ 0.8Fe203

(1)

2) Aluminium modulu s

- Demand report s. Most of this information is output both on the ope r ator te r minal and on a printer.

A1203 AM

(2)

Fe203 Control specifications

3) Silica modulus

The aim of the blending control system is to produce a full silo of s lurry wi th the desired cllemical composition as well as d minimum variation at the mill output, rejecting the disturbences c aused by Changes in the raw materials composition. This double objective can be formulated using a quality index expresed by the minimization of the slurry chemical average composition in the homogeneization silo. (Kevizcky, 1978).

CONTROL ALGORITHMS The slurry c omposition can be calculated, for an ideal process without delay, by means of the following equations:

[~l o r,

[Sl Se Sa 0j Cl Cc 0 Al Ac 0 FL FC 0

0 0 FP

[~~l

wr i tten in vector form : 0 = C x W

where C is the matrix of raw material s oxides compositions, 0 is the vector of slurry oxide contents (Si02, CaD, A1203 and Fe203 respectively ) and W the vector of the raw materials percent u a l weights ( lime, clay, sand and pyrite) . Moreover, s lu rry qual i ty is better expressed by relative rates of the oxide content. These relative rate s are:

Figu re 2 . Control scheme.

A1 203 SM

(3)

Al2 03 + Fe 203 These moduli are the variables to be co ntrolled . The drawback of c hoosing these output variables is that nonlinearities are introduced by the moduli Gomputation in the equations (1) , (2) and (3). This problem is solved in ( Al bertos 1985 a ) and (Morant 1985) by c hoosing suitable input variables. To a ch ieve an homogeneou s compos ition in the s ilo a number of solutions have been proposed by some re s ear ch teams. These solutions take advantage of the self-tuning adaptive co ntr ol approach to overco me the difficulty of disturbance measurement as well as the batch nature of the process. A general assumption is to <:: ons i der the raw material'3 c ompositions as an stochasti c disturbance. We propose to e s timate the raw materials co mposition fl-om ground analysis and to forecast the actual input of the park to the mill using a model ( Alber to s 1985b). The c ontrol strategy impl e mented in COMO i s based on a c ontrol loop with variable reference, the raw materials composition being estimated by an on-line estimator feeded by the results of the X-ray dnaliser and average information on the raw materia l s parks. The control scheme, described in detail in ( Mo rant 1985) and ( Albertos 1985a ) , is shown in figure 2.

P. Albertos, F. Morant,

104

J.

A. de la Puente and A. Crespo

Rt., Fef'{' ne es

""' S .'
C0Illtt,
Figure 3.

Figure 4.

1'!'lIlln"llIl ...

Global structure

Hierar c hical Hardware dependence

defined as abstract data types with a set in et definition of operations specified part, wich is the only visible part. Implementation elet.,d 15 are hidden to is external modules. This methodology logical or used, too, to encapsulate defining physical peripheral devices general operations upon them.

In order to reinfor ce reliability aspects, fundamental in real time prograJll)lJing for industrial control appli c atiuns, the Modula-2 language (Wirtb, 1982) ha s been uSi2d. This language provides facilities for decomposing large programs into modules that can be separately written and compiled. Module definition is separated from implementation. So, it. i'3 ea s y t.o build abstract datd types in a way consistent. with the design me ·thodology. Modula-2 features include low level access to memory addresses, per ipher a 1 reg i s.ters and interrupts, which is nece:3sary handle the process interfa ce in

to a

desirable way. Real-time programming is supported by a standard multiprogramming kernel included in the standard module library. Ea ch of the subsystems shown in figure 5 is implemented as a concurrent task. The Analyser and Weigth tasks take care of communication, filtering, and other aspect s related to analyser and controller computers, respectively. The Operator task controls the man -machi ne interface with the operator. A CRT and a printer are used for this interface . The Mill task implements the control algorithm as desc ribed above.

PRACTICAL CONSIDERATIONS AND RESULTS Practical consideratio ns

The COMO program is working in a local This program has be e n cemerlt factor·y. PDP 11 with RSX11 implemented on a operating system. Besides

the control

p rogram

pe form::;

fu c tions,

supervision

the and

COMO alarm

funct.ion2- . For example, it detect s inte r ruptions in the flow of raw materials and tells the operator which weigth - feeder is stopped and for how long. It. can include maximum and minimum values for the variables to be c ontrolled, or detect an excessive delay between consecut ive analysis.

All

information related

and supervision processe s

to the control is printed and

stored . the contro l of the With this progra m, blending plant can be carried out in two under manual or different. forms When the manual automatic control. the control switched on control is program,

ac c ording

to

the

received

analysis, shows the adequate weightings to the operator, who manually makes the changes in the weight feeders settings. I f the automati c mode is switched on, the program performs all the funtions without any operator action. The o perator /s y stem interface has been implemented in such a way that he or she supervise the can , at any moment, blending process as well as decide about the control to be applied.

Results Mor-eover, a secondary task that periodically elaborates state reports, production statistics, historical reports, etc, is included in the system.

In a preliminary step, a complete mill plant has been simulated on the development computer and the proposed algorithm has been tested and verified. A full blending batch has been processed in the simulated plant. In order to test estimation the composition matrix silica contents in algorithm, the limestone and clay has been perturbed in

COMO: A Modula-2 Program The silo controller lYrv) generates the reference to the mill controller according to the actual silo average composition, the final desired composition and the limits imposed to slurry composition. The algorithm implemented is a simple proportional controller with limited output.

105

weigth feeders 'Oime, clay, sand and pyrite). This computer receives, through the serial link, the weigth feeder references and periodically sends to the main computer the actual feeder positions.

Software design methodology The mill controller lM.C) is a minimal variance controller and generates the desired oxide flows. The raw material estimator computes the expected raw material composition allowing the computation of set pOints for the raw materials local controllers. The mill dynamiC estimator block estimates the parameters of the mill.

SYSTEM DESIGN

Firstly, the global behaviour of the system was specified in a formal way. This specification of the system's functional requirements was written in the lenguage LOTOS '( ISO, 1985). This language has primarily been designed and used for specifying communication protocols, and is based on the CCS model of concurrent computation '(Milner 1980). A variant of the ACT-ONE language (Ehrig & Manr, 1985) has been included in LOTOS in order to provide abstract data type definition facilities.

Hardware configuration The hardware is configured in a two levels scheme as shown in figure 3. The first level includes a general purpose microprocessor with a multi-user operating system. This computer is a Micro PDP-11 under Micro RXS - 11M, a 512 Kb main memory and a 10 Mb hard disc. A total of 6 serial lines are available. Two of these are used for the operator interface lCRT and printer), and two more ones for communication with the level 2 computers. The second level includes two microcomputers linked to the main computer through the above serial links. One of the microcomputers is embedded in a commercial X-Ray analyser. This computer has attached a local printer for analysis output. The same output is sent to the main computer, which extracts out the relevant Slurry composition data. The other microcomputer acts as a local actuator computer that provides analog input and output for controlling the four

The specifation has been used to provide a formal semantics to operator commmands and to describe the observable behaviour of the control system . More details can be found in (de la Puente, Crespo & Perez, 1986). Figure 4 shows the global structure of the systems as speCified. The arrows denote communication channels. The global specification is useful to express the general aspects of the desired behaviour. However, a structured decomposition with a number of subsystems is more convenient and efficient for the design. Each of this SUbsystems will be a process or task in a concurrent scheme. Figure 5 shows the control decomposed into subsystems.

An object oriented methodology has been used for the design phase. In this methodology, objects as raw materials, compositions, weigth positions, etc, are

Wcigths Feeder-s

Figure 5. SUbsystems decomposition

system

106

P. Albertos, F. Morant,

two different process

forms,

during

J.

A. de la Puente and A. Crespo

the blending REFERENCES

1) step variations The silica contents in limestone and clay have a strong variation in the second hour. I n the figure 6 we can see the bebaviour of the blending process when there are not estimations. When estimation is present the silica contents deviation at the mill output is decreasing and the composition is more homogeneus in the silo as it is shown in figure 7. The desired reference is reached at the end of the batch process ing. 2) sine v ariation As in the previous case we can see the blending of the batch when the silica contents in limestone and clay has senoidal variations. We can see that the s lurry gets the target much better when the estimator bl ock is used, fig 8 and 9. Sample results of a real blending with the COMO pt' ogram in the fa ctory are summarized in table 2.

A complete computer program for slurry mill contr'ol in cement plants has been developed. The program implements an ad-hoc control algorithm in order to keep sta ndard deviations at the slurry s ilo small. Simula 't i ons and prel imina ry on site experiences have shown the validity of the approach . soft ware start ing

techniques,

s pecificat. i oI1S I

and

design with 't he

design form"l

use

of

developrnent~

times.!1s

well

L=tS

et

good

''Juali ty software produ c t. In

particular,

Modula-2

i :5

a

Ehrig, H. • and Mahr, B . '(1985). fundamental of Algebraic Specification L Equations and Initial Semantics. Springer-Verlag. ISO,

Information Process ing Systems Definition of the Temporal Ordering Specification Language LOTOS, TC97/SC21/WG16-1 N29 ~. ~1984).

Keviczky, L. control blending. 525-532

(1978) . Self-tuning adaptive of ceInent raw material Automatica. Vol 14 pp

Morant, F., and Albert os , P. (1985).Model reference control of a cement mill. IFA<=;' Conference on Digital Contro~ Appl ieat ion s :to proc e.§.§. co ntra l . Wien. de la Puente, J.A . • Crespo, A., Perez, T. (1985) . Formal specif i cat ion of real-time systems. An industrial example. Repor~ SIC-86 / 1 . Departamento de Sistemas Informaticos y COlIJputaci6n.

a

structured con.; u rrent programming langu age have proved to be very u se ful in getting short

Albertos, p" and Morant, F . ·<1985b). An algorithm for parameter estimation with multiple indefinided solutions. The blending problem. 7th ~ on Identification and System parameter estimation . (IFAC/IFORS). York.

Mi ln er , R. (1980). b.. c alculus of cOlIJJIluni cat ing §}'stems. Springer-Verlag

CONC LUSION

Sy s 1:e mati.~

Albertos, P., and Korant, F. <1985a). Cement raw material blending: an adaptive control strategy. lEE Symposiun Control 85. Cambridge.

the autho rs find that very well suited langua6e

for '3mall to mediuID siz,,=, real-t ime software systems programming. featuring many of the go od aspec.ts of Ada wi th significantly smaller complexity and a wider availability, at least for this moment.

ACKNOWLEDGEMENTS The development of the CO MO program ha s been partially supported by a resear ch contra ct bet ween the Universidad Politec nica de Valencia and the Compania Valenci ana de Ce mentos Portland S.A.

Wirth, N. (982) ProgrammiI2& in Modula -2. Sprinser-Verlag.

107

COMO: A Mod ula-2 Program

.......:./ . ....

-..... .........

~

~~

~.r ....

.'

.... ......._........ .....

.......\ ........ ,

1h

. .... .

..

211 ", "' ,. ..........".,.

....... '

?.

-......... ......................... -... . ,

.. .. ... I! ..... _,. ..........4h. ... ,. ...... ,. . . ~ ~r"" ·

'80 80

Figure 7. L. M. composition with estimation. Step variation. a) Mill output<.); b) Silo output<+l

Figure 6. L. M. composition with out estimation. Step variation. b) Mill output< . ) ; b ) Silo output <+ )

,b

......

........ .

.... '

"

..,,,,, .....

~

.....

F iSUl'e <:;. L. M. composi t ion wi th E.'stjmation. Sine va.riation. al }!ill out-putc . ); b) Silo output(+)

Figure 8. L . M. co mposition without estimation. :...7)ine variation. a) Mill output(.); b> Silo out put <+>

Table 3.

Real results of

:t~. blendins.

L! .::'::'

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12:03

1~ : 29

13 : 2 3 1 4 : : :

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16:06

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44.8:

2.32 44. 7~

12' . 30 3.48 2 . 37 44,49

12 . .;.0

2.23

12.31 3.46 2.35 44.71

12.4~.

~ . 5':·

• 2 . ?S 3".5:

3 . 45' 2.40 44. 2.l1

4<:.09

C .57 0 .06 0.40 0.28

O. : ..:, 0.06 0 . 41

0.56 0.06

0.29

0 . 39 0.29

0.35 0.06 0.39 0.29

0 . 00 0.38 0.29

o .~6

0.28

0.5.: O. Co .: 0.40 0.29

0, co 0.06

0.40 C .29

64.36

64.43

64.40

64.23

64.2~

64 . 26

64.27

64.31

64.34

6 4 .4 1

2.38

2.22

2.20

2. I ~

2.13

2.12

2.! 2

2.1:::

i. . 6i.

1.::';

102.74

1 . 61 1 06, ~5

2. ;.3 1.52

107 . 21

Ill. 10

I l l . ;'1

1.5i 111.46

1 • ~6 III ,~2

1 . 47 110.34

109.10

107 . .s5

5':: . 8 0 -5.14

'5.:..73

61.78

0. 76 16.62

6. ;'9 16.69 4. ~, 3

61 . A4 -11 . 34 5 .1 9 ? .1 4 1"6 . 67 ~. 02

6(1.21 -9 . 90 5 .21 7.20 16. ?2 4.86 128 . 04 0.32

~B.:!j

5 . 73

61. ! ~ -10.63 5.45 0. 95 1 6.57

62.04 -1 1 .4S

S.7 1

120.:29 0.32

56 . ~3 -6.51 ~. 31 7.29 17.34 4. ~2 124.83 0.3 1

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22.12 2.94 1.00

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