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A graphical rule language for continuous dynamic systems

A Graphical Rule Language for Continuous Dynamic

Systems

Alonso G′o nzalez,Carlos J.Rodr′?guez Diez,Juan J.

Departamento de Inform′a tica

Universidad de Valladolid

Spain

e-mail:{calonso,juanjo}@infor.uva.es

Abstract.A graphical language to represent rules is described.It

has been designed for on-line applications on continuous systems.Rule

conditions are represented using pipe diagrams and its edition is simple

enough for a non-expert computer user.In order to use this language in

dynamic systems,elements to deal with uncertainty and time has been

introduced.Temporal expressions involving quali?ers like“always”and

“generally”over fuzzy sets like“x is high”are available.The syntax

and semantics of these primitives and of their combination is presented.

The graphical representation and edition of the previous elements is

discussed.An application based on this language has been developed

to allow the user to adapt the operation of a monitoring and diagnosis

system.The methodological approach to the application development

is brie?y discussed.

1Introduction

A di?culty in the generalised use of Knowledge Based Systems(KBSs)in some impor-tant domains is the necessity of constant update.This is particularly true in industrial applications,where factories with the same purpose may be very di?erent.Even the same factory can vary strongly its operation with time.

After some experience with KBSs working on line on continuous processes[2,3],it became evident that a necessary condition to obtaining full operative KBS applications was that system update and maintenance of the knowledge base must be done by the end users[11],experts in the domain but not professional programmers.And we thought that the basic step to achieve that objective was to endow the end user with a tool that supported a graphical,visual,language which allowed references to the basic concepts used by the users to reason about the problem domain.

Since most knowledge in expert systems is expressed with rules and this concept is simple enough to be understood by a user,we opted for a visual rule language.A visual environment is nowadays assumed,but visual languages[5,6]are less https://www.doczj.com/doc/565261929.html,ing a visual language to express rules allows a more intuitive programming and maintenance, even for a non-expert computer user.The same language can be used as a debugging mechanism and as an explanation aid to the user.The notation chosen to represent rule conditions was based on directed acyclic graphs,where the nodes are simple conditions. They allowed expressing simultaneously the logical(conjunction,disjunction)and the temporal issues(sequentiality,parallelism)of a condition.

In a language designed for continuous dynamic systems some consideration,regard-ing uncertainty[9]and temporal aspect[7],must be done.Keeping in mind that we

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wanted to represent sentences like“between8:00am.and8:30am.the pH was high”or “during the last three hours there has been some shortage of fuel”,we opted for a fuzzy logic[13,14]approach to uncertainty.A discrete linear point based time model was se-lected[1],allowing references towards the past with time stamps relative to the present evaluation time.Nevertheless,approximate values at precise time points weren’t enough to capture the rich temporal language commonly used at a factory control room.It seemed that vague properties held during time intervals were highly signi?cant.Hence, we extended the temporal model de?ning some fuzzy quali?ers[8],which operate on fuzzy values over time intervals.Another interesting temporal element is the possibility of future references.This is possible with the use of waits.

The paper is organised as follows.The language primitives and their combination to form rules in Sect.2.Section3discuses the graphical representation of the previous elements.An application that uses this language and some topics about its development are presented in Sect.4.Finally,Sect.5concludes.

2The Language

The majority of the data to be processed in a dynamic environment are temporal series arising form sensor interfaces.As we needed fuzzy values over historical sensors data, we de?ned indicators,which kept the present and past values of sensors,although an indicator value might be de?ned applying a function to any set of measurements. Indicators had associated situations,that allowed to de?ne fuzzy sets over the sensors’range.In this way,we paved the way to represent sentences like“the pH was high at8:00 am”,providing the time reference were in the scope of the historic data maintained by the indicator and assuming that the fuzzy membership function was time independent. In Table1is shown the structure of a situation-de?nition;the functions supported were the ramps(ascendant and descendant),that need two arguments,and the trapezium (4arguments)

Five temporal quali?ers(Table1)were de?ned.Now and Ago operate over fuzzy membership values at time points.Sometimes,Always and Generally operate over collections of membership values,for the same fuzzy set,in a time interval.Sometime is true in an interval if the variable have an historical value that is true,it could be considered as a multiple‘or’and its value is the maximum of all the values in the interval.Always is true if all the values in the interval are true,it’s the‘and’extended, and its value is the minimum of the values in the interval.

Generally pretends to express the idea that a logical variable is true most of the time,and it wasn’t so clear how it must be de?ned.The?rst consideration was that if a variable stayed constant in an interval,then“generally”of this variable must be equal to the value of the variable.The second extreme case considered was when all the values of the variable in the interval had values0or1.This is the same situation that if we were working with classical logic.If the variable is always true then“generally”of this variable will be true.If the variable is false more than the half of the time,then we can say that generally of the variable is false.This suggested that a ramp membership function could be used.Then,the chosen formula was:g(x)=max 0,1?s where

x.If s=0.5(its maximum value)then g(x)=max(0,2

3 situation-de?nition→situation‘for’indicator‘is’

((‘ascendant-ramp’|‘descendant-ramp’)

‘(’number‘,’number‘)’

|‘trapezium’‘(’number‘,’number‘,’number‘,’

number‘)’)

temporal-quali?er→‘now’

|temporal-point‘ago’

|(‘sometime’|‘always’|‘generally’)

(‘between’temporal-point‘and’|‘since’)

temporal-point‘ago’

temporal-expression→temporal-quali?er[function]

(functional-expression|indicator‘is’situation) simple-condition→temporal-expression|wait

|subcondition|procedure-invocation

subcondition-de?nition→subcondition‘is’compound-condition

compound-condition→simple-condition

|compound-condition(‘and’|‘or’)compound-condition

|‘not’compound-condition

antecedent→compound-condition

consequent→{action}

rule→antecedent‘implies’consequent

Table1:Grammar

values and it’s applied to every historical point in the interval.The typical example is the“not”operator,in expressions like“generally not(x)”.Moreover,it’s also possible to apply these quali?ers to functions,like“x2>a”,without de?ning an indicator(and keeping its historicals)for x2if we have an indicator(and historicals)for x.

A temporal expression was a simple-condition.They could be combined using con-junction,disjunction and negation to form compound conditions.Nevertheless,not every property of classical logic extend to that formalism.For instance,conjunction isn’t commutative and idempotence no longer holds:if a is a condition,it isn’t always the same as a∧a(i.e.,a is“wait5minutes∧b”).

Moreover,there are other types of simple conditions.A wait condition always is true,but the result is given only after a period of time has elapsed.This was useful to test a sequence of conditions,when some of them were expected to occur in the future. It was also possible to work with subconditions,that were references to compound conditions.As a last resort,another type of simple condition was the invocation of a procedure,that returns a truth value.

A rule had an antecedent and a consequent.The antecedent was a compound condition,while the consequent was a sequence of actions.The possible actions were assignations,waits,rule invocations and procedure calls.The assignations could be deferred;an expression is evaluated and after a period its value was assigned to a variable.

3Graphical Representation

A compound condition could be seen as a pipe diagram,where the simple conditions act as valves.If the condition is true,the valve is open,and if the condition is false the valve is closed.The compound condition is true if there exists a path of open valves from the origin to the destination.The conjunction must be expressed connecting two conditions in serial,and the disjunction connecting the conditions in parallel.Figure1

4

Figure1:Graphical representation example

shows a diagram using this notation.

This representation was chosen because it’s more intuitive,for our users,than the logical gates representation.Moreover,it allows to express temporal issues(sequen-tiality,parallelism).A problem arose with the negation,because it hasn’t an intuitive correspondence in this notation.The selected solution was that the negations are only possible in simple conditions.This wasn’t so problematic because it’s possible to work with subconditions as another type of simple condition,and negate all the subcondition.

The condition editor initially showed two nodes,the initial and the?nal nodes. Also,there were so many buttons as types of simple conditions,that added a node representing a condition.Then,it was possible to edit the simple condition of the node, to place it,and to connect with other nodes.To work with temporal expressions was needed that indicators and situations were de?ned.An example of this de?nition is shown in Fig.2.

This notation was used by the user to introduce conditions,but also showed the result of the last evaluation of a condition.This was useful to give explanations to the user.Although fuzzy logic was used,in the tracing a three-valued(true,false and unknown)logic was employed.A simple condition could be unknown because its evaluation returned an unknown value or because it hadn’t been necessary to evaluate it to obtain the value of the composite condition.Di?erent colours were used to show the three possible situations of a simple condition.The connections between simple conditions were also coloured.When a connection went into a node,the output of this

5 node is the minimum of the value of the input connection and the value of the node. When two input connections are joined,the resulting connection has a value that is the maximum of the values of the input connections.Figure1shows three true simple conditions,one false and one unknown.The global result is true.

4Application and Development

This graphical rule language was conceived to support the development of an application designed to adapt the behaviour of a monitoring and diagnosis system[10],already in use at a factory control room,to the real plant working conditions.Monitoring systems are usually constructed considering a set of hypothesis that could be named nominal conditions.The purpose of this application was to allow the user to specify the operation of the monitoring system when the working conditions were not nominal. The graphical rule language was used by the user to specify what conditions weren’t nominal,and what must be done in these circumstances.Typical actions were to disable and enable elements(modules,alarms...)of the monitoring system.

States were used to describe the working conditions of the factory.An state could have rules to detect its input and its output.Simple conditions and actions were added to deal with states in the antecedent and in the consequent of a graphical rule.Then, the system could detect the input and output of states,although the?nal decision was left to the user.Di?erent colors were used in the states to indicate if the state is established and/or detected.The condition in Fig.1was the input of one of these states.

In order to understand and describe the underlying monitoring system,the experi-ence analysis of KADS[12]was used.Nevertheless,the application wasn’t an expert system,although it could be considered as a tool to develop expert systems.Hence,a most general approach to application development was taken,and UML[4]was used to do the analysis and design in an object oriented way.The application was developed using the Expert Systems Development Tool G2,because the underlying monitoring system was developed with this tool.

5Conclusions

This work has proposed a rule based knowledge representation language emphasising two aspects:its visual nature and a particular ontology.These characteristics seemed to be basic for the intended application domain:decision rules were mainly rules of thumb,main users were non programmers,and uncertainty and properties of temporal series were innate to the domain.

The visual nature of the language tried to tackled the problem of an extremely changing application domain,were the underlying physical layout might change every year and the operation protocol might change quicker.This required that the end user could e?ectively modify the knowledge base.Considering also that the?nal users pro?le was wide,from factory director to control room operator,a visual language with a clear semantic and easy to manipulate was clearly a must.We think that the visual language proposed is a suitable tool in such environment.

Another essential aspect was the ontology,or language primitives available to the end user.We looked for a small number of primitives that could capture the typical reasoning often employed by the control room personal.The developed set included only?ve temporal quali?ers,that also took uncertainty into account.The combination

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of this primitives allowed to express,in a very simple way,highly complex conditions. Although the nature and extend of this ontology requires further research,the end users found them highly natural and expressive.

The developed tool was used to design and implement a rather sophisticated appli-cation that allowed control room personal to adapt on-line a monitoring and diagnosis system to the real factory working conditions.The application detected the set of states that de?ned the factory global performance and adjusted the supervisory system ac-cording to the present situation.More over,the end user could de?ne the conditions to establish the states and the actions to be consequently taken.This was a satisfactory test on the language utility.

Acknowledgements.

This work was partially supported by Sociedad General Azucarera Espa?n ola S.A., SGAE.We are also indebt for the challenge of its development and the great num-ber of ideas that,specially,D.Manuel Bolla′?n,initiated and discussed with us. References

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