Синтез адаптивної системи управління нестаціонарними технологічними об’єктами харчових виробництв

Н. А. Заєць

Анотація


SYNTHESIS ADAPTIVE CONTROL SYSTEM OF NON-STATIONARY TECHNOLOGICAL OBJECTS FOOD PRODUCTION

N. A. Zaiets

 

Most of the processes of chemical and food industry management is multi dimensional objects with complex relationships between variables that are characterized by transience dynamic characteristics. This leads to a deterioration of the quality management systems standard because it depends on the dynamics of the object changes with time. There is a need to build controls, settings are changed (adapted) so that when changing object parameters accuracy and quality of the system remained unchanged.

Significant influence on the dynamics of facility management can exercise its nonlinearity mathematical model. Notethenonlinearitythatdictatedexactlydescribegrowthprocessesinthefacilitymanagement, whichinturncausedexcessivedemandsontheaccuracyofthecontrolsystem. Gototheappropriateobjectofnonlinearmodelsinhighmobilitysystem, whentheaveragetimeofregimechangecanbecomparedovertimetransients. Theactionofallthesefactorsleadstotheneedforadaptivemanagement. Themainfeatureofadaptivesystemsisthepresenceofthesepathsbywhichobtainedadditionalinformationabouttheconditionofthesystem, whichisusedtochangeitspropertiesintherightdirectiontoachievetherequiredperformanceandoptimalmanagement.

Continuityofoptimalcontrolcanbeachievedbysynthesisofadaptivesystemswith a referencemodel, whichdescribesthedesiredoutputtargetmanagementsystemfor a giveninputaction. Butthedrawbackofthissystemisthecomplexityofthewithdrawalofthereferencemathematicalmodelthataccuratelyandcompletelyadequatelymeetstheobject. Therefore, inthecasewhentheunknownmathematicalmodelusedadaptivesystem ID inwhichthesynthesisofadaptingcircuitbyusing a specialdevice - identifier. Duringtheoperationofthefacilitymayberevisedasthestructureofthemathematicalmodelanditsparameters, iethemodelitselfisadaptiveandidentificationprocessonlinefeedback.

Thestudyisstructuringautomatedcontrolsystemusingadaptivesystem ID.

TheobjectoftheresearchconsiderdiffusionplantsugarfactoryequippedColumndiffusiondevice, characterizedbynon-stationary, unfavorablepropertiesasfacilitymanagementandisdecisivetechnologicalapparatusofwhichdependsontheefficiencyofthecomplexas a whole.

Thecontinuousdiffusioncurrentstationconsistsof:

- Columndiffusionapparatus;

- Oshparyuvachabeetchips;

- Heatersforjuiceandwatersupply.

Maintaintherequiredtemperatureinthediffusionapparatusisdecisiveindicatorofthequalityoftheextraction. Intermsofbasicautomationadjustablevariablesaretopofthecolumntemperatureandtemperatureshparyuvachi, keepingthemat a givenlevelisbyregulatingsteamflowtotheheaterjuiceandwatersupply.

DevelopmentofAdaptiveautomatedcontrol ID includesthefollowingsteps:

1. Determiningthestructureof a mathematicalmodeloftheobject.

2. Calculationofthemathematicalmodeloftheobject.

3. SelectionAlgorithmregulationthatwillprovidethenecessaryqualityofthesystem.

4.Selectionalgorithmofoptimalcontrollersettingsbasedmathematicalmodeloftheobject.

5.DevelopstructuresAdaptiveautomatedcontrolstationdiffusionanditsimplementation.

Todeterminethestructureof a mathematicalmodeloftheobjectwasconstructedandanalyzedparametricdiagramofthemajorthermaldiffusionprocessesintheplant. Houseidentifiedthreetanks: oshparyuvachacapacity, thecapacityofthebottomofthecolumn, thecapacityofthetopofthecolumn.

Becausestructureparametersandmathematicalmodelgreatlydependsonthecoefficientofheattransfer, volumeworkenvironment, heat, modeofobjectchangein a widerange, thereistheproblemofdeterminingtheidentificationoftheperiodforwhichthedefinedmathematicalmodeladequatelydescribesabout ' object. Theexperimentaldatadeterminedthattheperiodofcalculationofthemathematicalmodelis 25 minutes.

Tomaintain a giventemperatureoftheobjectappropriateuseofstandardlinearregulationlaw, includingproportional-integralalgorithm. Andintheadaptiveautomaticcontrolunitcalculatestheidentificationofoptimalcoefficientstransmissionsettingsregulators, leaving a constantintegrationtime.

Thealgorithmcalculatingtheoptimalsettingscontrolscanbeselectedfrom a numberofsearchmethods, includinggradient, nogradient, randomsearch. Atthesametimeasthesearchcriteriausedintegralquadraticcriterionspecifiedamountofvariationandtheactualvalues ofcontrolledvariablesthroughouttheperiodofadjustment.

Theinputdataforthedeviceadaptationareimportantvectorsofcoordinatesstateofficesdisturbances, aswellasdataonthestructureofthemathematicalmodelandtheperiodofidentificationcriteriaandmethodforoptimizingthesettingsoftheregulator, theoperatorelected a setofexistingones.

Developedadaptivecontrolsystemforautomated ID fortemperaturecontrolcontinuouslyactivediffusionplantsugarfactory. Thestudyhighlightedthestagesofsynthesisofadaptivesystemstargetedatstructuringautomatedcontrolsystemusingalgorithmsadaptation. Thesystemcanbeimplementedonthebasisofexistingtypicalmicroprocessorsystembyintroducing a deviceadaptation.


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Посилання


Kuncevich, V.M. (2006). Upravlenie v usloviyah neopredelionnosts: garantirovanie rezultati v zadachah upravleniya i identificacii [Management in terms uncertainty: harantyrovannыe results in problems of management and authentication]. Naukova dumka, 261.

Ladanyuk, A. P, Zaiets, N.A., Lutska, N.M. (2005) Zastosuvannya adaptivnih system keruvannya dlya nestscionarnih obektiv tehnologichnih kompleksiv neperervnogo tipu [The use of adaptive control systems for non-stationary objects such continuous technological complexes]. Automation. Automation. Electrotechnical complexes and systems, 1(15), 158-162.

Zaiets, N.A. (2010). Adaptivna sistema keruvannya temperaturnim rejimom roboti kolonnoi difuziynoi ustanovki [Adaptive control temperature regime of diffusion column installation]. Scientific Bulletin of National University of Life and Environmental Sciences of Ukraine, 148, 196-203.


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