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Closed-Loop Control Toolbox APP-RTT-E-GBOverview

Integration of open and closed-loop control inone PLC

The RTT closed-loop control toolbox offers around ahundred software function blocks for universal

control functions which can be individually puttogether, combined and set up for the task in hand.This enables solutions for both open and closed-looptasks to be combined in Sucosoft S 40 for oneautomation unit. Programming is carried out toIEC 1131-3.

The future belongs to closed-loop controlToday closed-loop control represents a fundamentalpart of the know-how of technical professions in thefield of process and production engineering. Thepurpose behind increasing automation is generally toraise quality standards and to increase the speed of

production, whilst at the same time reducing energylevels consumed. This is as true for the control ofoxygen levels in the aeration of a sewage plant as itis for temperature control in an extruder heatingzone.

It was only when software started to be used in theautomation industry ranging from the use of a PLCin a bottling plant to the process computer of a powerplant that classical technical control installationsand the still current DDC units came to be replaced bysoftware controllers. Today there is a desire to

network even simple controllers with each other in atotal system, to set their parameters from one processmanagement/control level, and where necessary, toadapt them even more closely to their requirements.

This can now be very easily achieved through the useof the RTT in a PLC.

Minimum programming requirement withoptimum functionalityThe RTT function blocks are designed to reduce theprogramming requirement for the user.The largeselection of function blocks with extremely simple

interfaces, ensures that this is the case. The followingselections, for example, are available for the range ofPID controllers:

PI controllers (see pictures for different controllernames)

PD three step controller

PID controller

Split-range PID controller (heating/cooling)

Autotuning PID controller

Each function block offers as much functionality aspossible. For example the PID controller offers thefollowing facilities:

Antiwindup procedure

Effective D-component computation(differentiation)

Standard control response (enables substitution ofexisting controllers)

Automatic determination of optimal scanningtimes for integrator and differentiator

Smooth (shock-free) acceptance of manualmanipulated variable

Current cycle time automatically taken into account

Implementation of function sequencesThe RTTs interpolation function blocks allow any

sequence of functions to be replicated. The accuracyof this replication depends essentially on the numberof interpolation points. 2, 3, 4, 10 and 20-pointinterpolations are available. If an interpolation isrequired with more than 20 interpolation points, thiscan be achieved by combining several interpolationfunction blocks.

PLC types supportedThe closed-loop control toolbox can be used on allPLCs which are programmed with Sucosoft S 40. Atpresent this applies to the following PLC types:

PS 4-150 (e.g. PS 4-141, PS 4-151) PS 4-200 (e.g. PS 4-201)

PS 4-300 (e.g. PS 4-341)

PS 416

Combining and linkingThe RTT can be used in many situations. For examplestandard function blocks such as PID controllers orpulse duration modulation, can easily be integratedinto a PLC program. However this represents only oneof the strengths of the closed-loop control toolbox.

The true potential of the RTT is fulfilled when differentfunction blocks are combined and linked to eachother. This enables advanced function blocks withspecial properties to be created, such as an adaptivefuzzy PID design for controlling boilers (see fig. 1).Individual users can quickly implement their ownideas even with their existing application know-how.

PLC function block libraryintegrates closed-loop andopen-loop control

Closed-loop controlsincrease quality and reduceenergy consumption

Function blocks with highfunctionality reduceprogramming work

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APP-RTT-E-GB Closed-Loop Control ToolboxOverview

Tried and tested applications

Among others the following tasks have beensuccessfully solved using the closed-loop controltoolbox:

Combined pressure/mixer control for de-icingairplanes.

Dosing control for the packaging industry

Chlorine control for indoor and outdoor swimmingpools

Controlling refrigerators in supermarkets

Controlling refrigerating plant for ice-skating rinks

Temperature control on extruders (heating/coolingin one zone)

Highly dynamic temperature control withautotuning

Control tasks in buildings, e.g. temperature,humidity, pressure and volumetric flow control

Fuzzy control of printing presses

Control designs for power plants

Control designs for sewage works

Temperature control for ball bearing test beds

Synchronisation control in drive technology

Modularity allows complexcontrol structures to be setup

Universal function blocksare suited to many areas

Figure 1:

Adaptive design for boiler control

T

T

Kp Tn Tv Kp Tn Tv

In let setpointtemperature

SetpointtemperatureFurnace Fuel

PID controller PID controll er

M aster con troller Auxi l iary control ler

Boiler

Inlet temperature

Fuzzy System

Furnace temperature

Ambient temperatureChange in heat required

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Closed-Loop Control Toolbox APP-RTT-E-GBBasic Principles

The principle of closed-loop control

The principle of closed-loop control consists in thevalue to be controlled being fed back from the placeof measurement via the controller and its settings

facility into the controlled system. The feedbackprocess makes this so-called controlled variable moreindependent of external and internal disturbancevariables, and is the factor which enables a desiredvalue, the setpoint, to be adhered to in the first place.As the manipulated variable output by the controllerinfluences the controlled variable, the so-calledcontrol loop is duly closed.

Technical systems process several kinds of controlledvariables such as current, voltage, temperature,pressure, level, flow, speed of rotation, angle ofrotation, chemical concentration and many more.

Disturbance variables are also of a physical nature.

These control loop terms can be easily explainedusing the familiar example of room temperaturecontrol by means of a radiator thermostat: therequirement is to keep the room temperature at22 C. This temperature is set by means of therotatable knob (= setpoint). The temperature (=controlled variable) is measured by a sensor. Thedeviation between the room temperature and thesetpoint is then measured by the built-in controller,often a bimetal spring, (= the control deviation), andis then used to open or close the valve (= themanipulated variable).

What are the disturbance variables? First of all thereis the effect of the outside temperature and the sunshining through the windows. The limitedthermostat can as little foresee these influences as itcan the occupants behaviour in opening a window orholding a party with a lot of guests who cause theroom to warm up. However this controller is still ableto compensate for the effects of one or moredisturbance variables, and to bring the temperatureback to the desired level again, albeit with somedelay.

The principle of open-loop control

Open-loop control is to be found wherever there is noclosed control loop. The biggest disadvantagecompared with closed-loop control, is that unknown

or non-measurable disturbance variables cannot becompensated. Also the behaviour of the systemincluding the effects of disturbance variables whichthe open-loop control system is able to measure,must be exactly known at all times in order to be ableto use the manipulated variable to influence thecontrolled variable.

One advantage is that an open-loop control systemcannot become instable as there is no feedback thisis a problem of closed-loop control.

Classification of closed-loop systems

Closed-loop systems are not classified by the physicalvalues to be controlled, but by their behaviour overtime. The level in a container can thus bemathematically described in exactly the same way asthe voltage of a capacitor.

Behaviour over time can be determined for exampleby abruptly changing the input value and thenobserving the output value. Knowledge of the basiclaws of physics is often sufficient to estimate thisbehaviour. Only in relatively few cases is it necessaryto calculate it.

Figure 2:

The principle of closed-loop control

Closed-loop control hasadvantages over open-loopcontrol

SetpointSetpointdeviation Closed-loop

controllerM anipulatedvariable

Disturbancevariable

Control systemProcess variable

Figure 3:

The principle of open-loop control

Figure 4:

Control system with delay

SetpointM anipulatedvariable

variableOutput

Open-loopcontroller

System

M easurabledisturbance

variable

Unknow n and

unmeasurabledisturbancevariable

Input variable

Systemw ith delay

Output variable

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APP-RTT-E-GB Closed-Loop Control ToolboxBasic Principles

The behaviour over time of a closed-loop system isnormally characterised by the fact that when theinput value is abruptly changed, although the outputvalue immediately begins to change, it reaches itsend value with some delay.

Closed-loop systems are further distinguished bythose with and those without self-regulation.

In a system with self-regulation, after the suddenchange in the input value, the output value assumesa constant value again after a period of time. Suchsystems are usually called proportional systems or Psystems. Let us take the example of a heating zone:the input value is the electrical heating power, andthe output value is the zone temperature.

In a system which does not have self-regulation, theoutput value will rise or fall after the abrupt changein the input value. The output will only remain at a

constant value if the input is at zero.Such systems are usually called integral systems or Isystems. A example of this is a level control in acontainer: the input value is the incoming flow, theoutput value is the level of the liquid.

Another important type of system is a system withdead time. In this case the input value appears at theoutput after the dead time delay. In a technicalsystem the dead time is the result of the distancebetween setting and measuring locations. Example of

a conveyor belt: the input value is the quantity ofmaterial at the beginning of the belt, and the outputvalue is the measurement of the amount at the end ofthe belt. The dead time is calculated as the length ofthe belt divided by its speed, and it can therefore vary.

In all the different systems discussed which arenormally found in combination, we are dealing withso-called linear single variable systems because thereis only one output value (= the controlled variable) aswell as one input value (= the manipulated variable),and the system possesses linear properties.Controllers for these very common systems areaccordingly known as single-variable control systems

and are provided in the closed-loop control toolbox.

Figure 5:

Control system with self-regulation

Figure 6:

Control system without self-regulation

Input variable Output variable

System w ithself-regulation

self-regulationSystem w itho ut

Output variableInput variable

Figure 7:

Control system with dead time

The RTT can be used formany closed-loop controlsystems

Input variable

dead t imeSystem w ith

Output variable

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Closed-Loop Control Toolbox APP-RTT-E-GBBasic Principles

Types of controller

The controllers examined here are divided into twogroups:

Discontinuous controllers only offer 2 or more

fixed values as the manipulated variable (in the RTT:two-step and 3-step controllers). They are suitable forelementary control tasks in systems with large delays.

Continuous controllers can offer every technicallypossible value as the manipulated variable. Thesecontrollers are classified according to the reactiontime of the manipulated variable in response to thecontrol deviation at the input:

The proportional (P) controllergenerates amanipulated variable only consisting of the positiveor negative control deviation (the parameter is the

transfer coefficientK

p). In a proportional differential (PD) controller a

component is added to the manipulated variablewhich is proportional to the change in the controldeviation (the parameter is the derivative actiontime Tv).

In a proportional integral (PI) controller on theother hand, a component is added to themanipulated variable which is proportional to therunning total control deviation (the parameter isthe reset time Tn, inversely proportional to time!).

The proportional integral differential (PID)

controller combines all the above functions, andis therefore often used. Its advantages: it reactsquickly to a control deviation and acts in such away as to ensure that the control deviationdisappears. The emphasis on the individual controlcomponents depends on how the parameters areset.

The closed-loop control toolbox offers all these typesof control.

Which controller for which system?The best controller has been selected and theparameters correctly set when the control deviationdoes not exceed a specific value and the controllernever oscillates.

The engineers task is to select the type of controllerbest suited to the closed-loop control system, andthen to find the best possible parameter settingswhen commissioning it. The following table showsthe basic suitability of the controllers:

Symbols: not suitablek not particularly suitable+ suitable(+) suitable but with limitations

When is a fuzzy controller used?The fuzzy control function blocks contained in theclosed-loop control toolbox can be best used for

processes with non-linear behaviour, as thesefunction blocks allow non-linear controlcharacteristics to be set,

contradictory control objectives,

processes heavily affected by dead time,

multiple variable control,

processes which cannot be adequately describedby a mathematical model,

those cases where the controllers described abovedo not give satisfactory results.

The RTT offers all currenttypes of controllers

In some cases fuzzy functionblocks make sense

System P PI PD PID

with self-regulation, deadtime only

+

with self-regulation, deadtime with delay

k +

with self-regulation,single delay

(+) (+) k k

with self-regulation,multiple delay

k +

no self-regulation, singledelay

k k (+) (+)

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APP-RTT-E-GB Closed-Loop Control ToolboxTechnical Details

The three-level structure of the functionblocks

The closed-loop control toolbox (RTT) is hierarchicallystructured and consists of three levels (figure below):

First level:Mathematical and logical functions arecarried out on the ground level. It is especiallyimportant here that maximum accuracy withminimum cycle time is achieved on the basis of thetype of controller used.

Second level:The basic function blocks of

closed-loop control technology have been assembledhere such as integrators, differentiators, PT1 or deadtime elements. These access the functions of the firstlevel.

Third level:Complex control technology algorithmsare implemented on this level on the basis of the twolower levels. Here there are function blocks for thefollowing areas: linear controllers, fuzzy controllers,pulse duration modulation, signal processing andsystem simulation.

Linking and setting parameters

Using the function blocks, applications can becombined in the PLC program. For this the finishedfunction blocks are instantiated, i.e. individual namesare allocated to each function block. (e.g.PID_controller_zone_1).

All that remains is to link the inputs and outputs ofthe function blocks in accordance with the technicalcircumstances (see example on page 10), and to setup suitable parameters.

What happens in multiple instantiation?Multiple instantiation of a function block (e.g.PID_controller_zone_1 to PID_controller_zone_20)can be effected in order to set up several independentor cascaded controllers: in this way large-scaleclosed-loop control tasks can be solved in a PLC.

The clever part about the system: only one code rangeis used in the whole program for the function blockused, e.g. the PID controller, but in the case ofmultiple instantiation it is processed for theappropriate number of instances. Only the data rangefor individual control data (e.g. integral anddifferential components) which have to be storedtemporarily from one call procedure to the next, isautomatically stored separately for each instance ofthe function block.

For this reason the additional memory requirement(given in the documentation) for multiple

instantiation of a function block is low.

Single instantiationIf a function block does not have to store any data forthe next call, it is sufficient to only instantiate it once(allocation of only one instantiation name in thedeclaration section), and if it is required more thanonce, to call it up several times in the instructionsection. Typical examples are the mathematicalfunction blocks, the interpolation and fuzzy functionblocks.

Multiple usage only requires the memory for one

function block instance.

Figure 8:

Three-level structure of the RTT function blocks

Level 3

Level 2

Level 1

D control ler

ConversionM ult ip l ication

I controller

Clock generatorAddit ion Lim itat ion

P controller

PID controller

Modular function blockstake up less programmemory

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Closed-Loop Control Toolbox APP-RTT-E-GBTechnical Details

Self-explanatory variable and function blocknamesThe chosen variable and function block names of theRTT are described in detail and are self-explanatory sothat programmers can use the RTT without any

lengthy familiarisation required. Most of the functionblocks can be integrated into the user program andassigned parameters without the aid of thedocumentation.

The function block names are structured as follows:

All function blocks begin with the symbols U_,making for a unified listing system.

There follows an abbreviation which arranges thefunction blocks alphabetically into areas(in casethere are several of the same type), all fuzzyfunction blocks for example beginning with

U_FUZ. If there are several function blocks of the same

type, distinguishing codes are added in front of thename, e.g. interpolations with data type UINT orINT (see below).

At the end there is a descriptive name for thefunction block, e.g. PID_controller.

Examples of function block names are:

U_LMA_INT_limit_monitoraLimit monitor fordata type Integer

U_LMA_UINT_limit_monitoraLimit monitor for

data type Integer U_IP20_UINT_INTERPOLATIONa20-point interpolation for data type unsignedInteger

U_IP3_INT_INTERPOLATIONa3-point interpolation for data type Integer

Variable names are structured as follows:

At the beginning there is a descriptive name, e.g.setpoint.

There follows (if useful) the unit or resolution, e.g.12Bit, percent or ms.

At the end of the variable name is the data type,e.g. INT, UINT or BOOL.

Examples of variable names are:

Reference_value_12Bit_UINT

Ramp_time_ms_UINT

Tn_10ths_UINT

Setpoint_12Bit_UINT

Self-explanatory namesreduce the effort requiredfor program familiarisation

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APP-RTT-E-GB Closed-Loop Control ToolboxTechnical Details

Documentation of a function block interface

U_PID_controllerPID-controller with 12-Bit inputs and outputs

Prototype of the function block

Meaning of operands

The RTT can almost be usedwithout a manual

U_PID_controller

Inputs Outputs

UINT Setpoint_value_12Bit_UINT Manipulated_variable_12Bit_UINT UINT

UINT Actual_value_12Bit_UINT

Parameters Monitor outputs

BOOL P_activate_BOOL Manipulated_variable_P_13Bit_INT INT

BOOL I_activate_BOOL Manipulated_variable_I_13Bit_INT INT

BOOL D_activate_BOOL Manipulated_variable_D_13Bit_INT INT

BOOL Accept_manual_manipulated_variable_

UINT Proportional_rate_P_percent_UINT

UINT Reset_time_10ths_UINT

UINT Derivate_action_time_10ths_UINT

UINT Manual_manipulated_variable_12Bit_UI

Designation Meaning Value Range

Inputs

Setpoint_value_12Bit_UINT Setpoint 0 to 4095

Actual_value_12Bit_UINT Actual value 0 to 4095

Parameters

P_activate_BOOL Activates the P-component 0/1

I_activate_BOOL Activates the I-component 0/1

D_activate_BOOL Activates the D-component 0/1

Accept_manual_manipulated_variable_BOOL

Smooth acceptance of manualmanipulated variable

0/1

Proportional_rate_P_percent_UINT Proportional rate +K

p[%] 0 to 65 535Reset_time_10ths_UINT Reset time Tn[0,1 s] 0 to 65 535

Derivate_action_time_10ths_UINT Derivative action time Tv[0,1 s] 0 to 65 535

Manual_manipulated_variable_12Bit_UINT

Manual manipulated variable 0 to 4095

Outputs

Manipulated_variable_12Bit_UINT Manipulated variable (analog, 12 Bit) 0 to 4095

Monitor outputs

Manipulated_variable_P_13Bit_INT P component 4095 to 4095

Manipulated_variable_I_13Bit_INT I component 4095 to 4095

Manipulated_variable_D_13Bit_INT D component 4095 to 4095

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Closed-Loop Control Toolbox APP-RTT-E-GBDesigning

Design help

Because of the hierarchical and modular structure ofthe RTT, calling up a single function block (FB) can initself entail considerable code sizes, data sizes and

instances. For example the PID autotuning controller,when called once, generates a code size of approx.41,500 bytes, 29 sub-function blocks and 84instances. However if further FBs are used which thePID autotuning controller has already used assub-function blocks, the code size does not increase.Thus when many RTT FBs are used, the relative codesize per function block decreases.

Due to the high functionality of RTT function blocks,the cycle time requirement is relatively high whenPS 4-200 controllers are used. For example a PIDcontroller requires approx. 16 ms PLC cycle time. If for

example 30 control zones are set up, considerablePLC cycle times occur, or the maximum cycle timemay be exceeded. In such cases the program can besegmented (as long as the control system is slowenough), with the result that per PLC cycle only onecontroller zone is called.

The cycle time requirement when using a PS 416 orPS 4-341 is 20 to 60 times shorter than for thePS 4-201!

Sample programsAmong the sample programs available for the

closed-loop control toolbox are the following: PID controller combined with pulse duration

modulation for 10 zones

PID controller combined with simulation

PID autotuning controller combined with PTnsystem as a control loop simulation, with detaileddemonstration instructions

Adaptive fuzzy PID controller combined withsimulation and manual

An application example

Multiple zone temperature control is to be set up foran extruder: up to 36 zones which also influence eachother have to be simultaneously controlled. Thefollowing function blocks are necessary for theset-up:

PT1 Filter: The temperature sensor input signals aresmoothed and passed to the controller as actualvalues.

PID Split-range controller: Extruders are cooled

and heated in zones. Optimal control is only achievedif heating and cooling are processed in one algorithmwith two separate manipulated variable outputs.

Autotuning:Setting up the parameters for the PIDsplit-range controller can be done automatically withthe aid of the autotuning function block (see below).This function block sends test signals to the heatingand cooling units, and uses the reaction of thetemperature loop to calculate the best parameters forthe PID split-range controller.

PDM:The PDM function block converts both of the

analog controller manipulated variables into pulseduration modulated, digital signals. These signals canbe used to directly switch the contactors orsemiconductor relays of the heating and coolingunits.

Cycle times decreasethrough sensibly plannedfunction block calls

Sample programs offergood ideas

Figure 9:

Temperature control design

Auto tun ing

SET temperatu re PIDsplit rangecontrol ler

PDM

PT1-fi l ter

ACTUAL temperature Temperaturesection

PLC

Cooling

Heating

Disturbance variable

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APP-RTT-E-GB Closed-Loop Control ToolboxDesigning

Commissioning a controller

When a PLC program is loaded with an untestedcontroller, the control loop should not be closedimmediately. Before a control loop can be started up,

the whole technical environment, i.e. automationunits, actuators, sensors, etc., must be set up andtested. Special attention must be paid to whether thecontroller function block is receiving the rightreference and actual values, and to whether actuatorsare being controlled as planned by the manipulatedvariable. Scaling and polarity may have to beadjusted.

Now the controller must be set up:

If parameters are already known, these can beused.

In a PTn system, the autotuning controller can setits own parameters automatically. It is enough touse this powerful function block only for thecommissioning phase and then to replace it withthe PID controller.

The reactions of the control loop (controlledvariable) can normally be recorded by abruptlychanging the manipulated variable (transferfunction). The self-regulation and delay times sodetermined can be used to calculate suitable,rule-of-thumb parameters.

When selecting the best parameters, it should beborne in mind whether the control loop will have tocompensate more for disturbance variables or morefor changes in the setpoint (termed fixed setpointcontrol or sequential value control).

The control behaviour can be further improved byincluding the disturbance variables in the controlprocess. An interference value can either be directlymeasured, or it can be correlated with ameasurable state of the process.

If the characteristics of the control system change(mass, volume, thermal properties, etc.), thecontrol parameters can be seamlessly adapted viaa fuzzy function block, or in the simplest of cases asecond set of parameters can be selected.

Autotuning the PID controller

Autotuning, i.e. the automatic determination ofcontrol parameters by the PLC program, is suitable forPTn loops. At the beginning of the autotuning

process, a manipulated variable is given a steppedchange, and the response from the control loop isthen evaluated using the inflectional-tangentmethod. The actual value reaches the setpoint bysetting parameters in the PID controller. After this thefinal parameters are set for the PID controller.

Simulations often make senseSimulations can be set up very quickly for manyapplications using the RTT. It is therefore to berecommended to first simulate the application inorder to test the functionality of the controllers. Thefollowing function blocks are especially suited to

simulations:

Interpolations for implementing any number ofcharacteristics,

PTn systems, dead time elements,

Ramps, oscillations.

Visualisation and setting parameters

As a sensible extension of the RTT we recommend theuse of a visualisation and parameter setting tool. Amaximum range of 32 marker words can be read fromthe PLC via the Sucom A interface or EPC card, andprocessed as follows: numerical representation,graphic representation (visualisation) or saving toa file.

In addition a maximum range of 32 marker words canbe described. This function can be used, for example,for online parameterisation of controllers.

Further information on the visualisation andparameterisation tool can be found in thedocumentation.

PID controllers setparameters automatically

Simulations help to test thecontrol design in advance

Shorten set-up timethrough tested functionblocks

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Closed-Loop Control Toolbox APP-RTT-E-GBDesigning

Moeller GmbH e-mail: info@moeller.net 1999 by Moeller GmbHHein Moeller Str 7 11 Internet: http://www moeller net S bj t t alt ati

Overview of the RTT function blocks

The hierarchical, modular structure of the RTT offersthe following benefits:

Selective testing and optimization of self-contained

functions

Since function blocks of the upper levels mayaccess function blocks of the lower levels multipletimes, relatively small code sizes arise incomparison with non-modular programs

Complex algorithms can be implemented veryquickly by combining the modular functions.Because only tested function blocks are used, thenumber of programming errors is relatively low.

The basic functions are usually set up for data typesInteger and Unsigned Integer. The following function

blocks (approx. 100) are available: Basic mathematical functions:

Fractions

Moving average

Sine, cosine and tangent

Inverse of sine, cosine and tangent

Exponential functions, square roots

Other basis function blocks:

Interpolation with 2 to 20 X/Y interpolationpoints

Sunrise/sunset data (only for places in Germany) Counters

Calculation of average cycle time

Automatic constant cycle time

Display current/maximum cycle time

Simulation:

PTN control systems with input of systemorder/system parameters

Basic function blocks of closed-loop controltechnology

Scanning time generator

Differentiation, integration

Proportional amplification

Ramp function

Triangular/sinewave/sawtooth oscillation

Hysteresis element, threshold value

Splitting of a bipolar input value

Dead time delay

Delay system 1. to 10. order

Setting procedure for PID controllers

Controllers:

PI/PID controllers with 12-Bit inputs/outputs

PI/PID split-range controllers for heating/cooling

PID autotuning controllers

PD controllers with 3 step system for openingand closing valves

PD controllers with in-line integrator andself-regulation for 4 interference values

Two-step controllers, three-step controllers

Pulse duration modulation (PDM):

PDM with variable duration, suitable forcontactors

PDM for split-range processes, for contactors

PDM to the noise-shape-method, suitable forsolid state systems

Signal filters, processing, limiting:

Limiting function blocks

Sensor for absolute limiting and warning values

Sensor for relative limiting and warning values

Sensors for relative tolerance ranges

PT1/PT3 filters for signal smoothing

Fuzzy systems:

Fuzzy systems with 2 to 4 inputs and 2 to 5 terms(partly REAL data type)

Programming to IEC 1131-3simplifies reuse

Large selection of functionblocks solves most controlapplications