Class UnitModel

Simulatable "default" process model.

This is a model that can be either dynamic or static, have one or multiple inputs and can be either linear in inputs or have inputs nonlinearity described by a second-order polynominal. Dynamics can be either 1. order time-constant, time-delay or both. The model also supports "additive" signals added to its output (intended for modeling disturbances).

The model is designed to lend itself well to identification from industrial time-series datasets, and is supported by the accompanying identification method UnitIdentifier.

This model is also intended to be co-simulated with PidModel by PlantSimulator to study process control feedback loops.

It is assumed that most unit processes in industrial process control systems can be described sufficiently by this model, and thus that larger plants can be modeled by connecting unit models based on this model structure.

It would be possible to extend this model to also describe second-order dynamics along the same principles by the introduction of one additional parameter in future work.

Inheritance

object

ModelBaseClass

UnitModel

Implements

ISimulatableModel

Inherited Members

ModelBaseClass.ID

ModelBaseClass.ModelInputIDs

ModelBaseClass.additiveInputIDs

ModelBaseClass.outputID

ModelBaseClass.outputIdentID

ModelBaseClass.processModelType

ModelBaseClass.comment

ModelBaseClass.x

ModelBaseClass.y

ModelBaseClass.color

ModelBaseClass.GetID()

ModelBaseClass.SetID(string)

ModelBaseClass.SetProcessModelType(ModelType)

ModelBaseClass.GetProcessModelType()

ModelBaseClass.SetInputIDs(string[], int?)

ModelBaseClass.AddSignalToOutput(string)

ModelBaseClass.GetModelInputIDs()

ModelBaseClass.GetAdditiveInputIDs()

ModelBaseClass.GetBothKindsOfInputIDs()

ModelBaseClass.SetOutputID(string)

ModelBaseClass.GetOutputID()

ModelBaseClass.GetOutputIdentID()

object.Equals(object)

object.Equals(object, object)

object.GetHashCode()

object.GetType()

object.MemberwiseClone()

object.ReferenceEquals(object, object)

Namespace: TimeSeriesAnalysis.Dynamic

Assembly: TimeSeriesAnalysis.dll

Syntax

public class UnitModel : ModelBaseClass, ISimulatableModel

Constructors

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UnitModel()

Declaration

public UnitModel()

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UnitModel(UnitParameters, string)

Constructor

Declaration

[JsonConstructor]
public UnitModel(UnitParameters modelParameters, string ID = "not_named")

Parameters

Type	Name	Description
UnitParameters	modelParameters	model parameter object
string	ID	a unique string that identifies this model in larger process models

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UnitModel(UnitParameters, UnitDataSet, string)

Initalizer of model that for the given dataSet also creates the resulting y_sim.

Declaration

public UnitModel(UnitParameters modelParameters, UnitDataSet dataSet, string ID = "not_named")

Parameters

Type	Name	Description
UnitParameters	modelParameters
UnitDataSet	dataSet
string	ID	a unique string that identifies this model in larger process models

Fields

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modelParameters

The parameters of the UnitModel.

Declaration

public UnitParameters modelParameters

Field Value

Type	Description
UnitParameters

Methods

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Clone(string)

Create a deep copy of itself

Declaration

public ISimulatableModel Clone(string IDexternal = null)

Parameters

Type	Name	Description
string	IDexternal

Returns

Type	Description
ISimulatableModel	deep copy

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GetFittedDataSet()

Returns a copy of the dataset against which the model was fitted.

Declaration

public UnitDataSet GetFittedDataSet()

Returns

Type	Description
UnitDataSet

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GetLengthOfInputVector()

Returns the number of external inputs U of the model. Note that this model may have a disturbance signal added to the output in addition to the other signals.

Declaration

public override int GetLengthOfInputVector()

Returns

Type	Description
int

Overrides

ModelBaseClass.GetLengthOfInputVector()

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GetModelParameters()

Get the object of model parameters contained in the model.

Declaration

public UnitParameters GetModelParameters()

Returns

Type	Description
UnitParameters	Model parameter object

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GetOutputSignalType()

Get the type of output signal.

Declaration

public override SignalType GetOutputSignalType()

Returns

Type	Description
SignalType

Overrides

ModelBaseClass.GetOutputSignalType()

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GetSteadyStateInput(double, int, double[])

Calcuate the steady-state input if the output and all-but-one input are known.

Declaration

public double? GetSteadyStateInput(double x0, int inputIdx = 0, double[] givenInputs = null)

Parameters

Type	Name	Description
double	x0	If no additive inputs y=x, otherwise subtract additive inputs from y to get x
int	inputIdx
double[]	givenInputs

Returns

Type	Description
double?

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GetSteadyStateOutput(double[], double)

Get the steady state output y for a given input (including additive terms).

Declaration

public double? GetSteadyStateOutput(double[] u, double badDataID = -9999)

Parameters

Type	Name	Description
double[]	u	vector of input values
double	badDataID

Returns

Type	Description
double?

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InitSim(UnitParameters)

Initalize the process model with a sampling time.

Declaration

public void InitSim(UnitParameters modelParameters)

Parameters

Type	Name	Description
UnitParameters	modelParameters	model parameters object

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IsModelSimulatable(out string)

Answers if the model can be simulated with the inputs provided.

Declaration

public bool IsModelSimulatable(out string explainStr)

Parameters

Type	Name	Description
string	explainStr	a string that explains why the model cannot be simulated if that is the case

Returns

Type	Description
bool

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IsModelStatic()

Is the model static or dynamic?

Declaration

public bool IsModelStatic()

Returns

Type	Description
bool	Returns true if the model is static(no time constant or time delay terms),otherwise false.

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Iterate(double[], double, double)

Iterates the process model state one time step, based on the inputs given.

Declaration

public double[] Iterate(double[] inputs, double timeBase_s, double badValueIndicator = -9999)

Parameters

Type	Name	Description
double[]	inputs	vector of inputs U. Optionally the output disturbance D can be added as the last value.
double	timeBase_s	the time in seconds between samples
double	badValueIndicator	value in U that is to be treated as NaN

Returns

Type	Description
double[]	the updated process model state (x) - the output without any output noise or disturbance. NaN is returned if model was not able to be identfied, or if no good U values have been given yet. If some data points in U inputs are NaN or equal to `badValueIndicator`, the last good value is returned

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SetFittedDataSet(UnitDataSet)

Store the fitted dataset.

Declaration

public void SetFittedDataSet(UnitDataSet dataset)

Parameters

Type	Name	Description
UnitDataSet	dataset

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SetModelParameters(UnitParameters)

Update the parameter object of the model.

Declaration

public void SetModelParameters(UnitParameters parameters)

Parameters

Type	Name	Description
UnitParameters	parameters

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ToString()

Create a nice human-readable summary of all the important data contained in the model object. This is especially useful for unit-testing and development.

Declaration

public override string ToString()

Returns

Type	Description
string

Overrides

object.ToString()

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WarmStart(double[], double)

Warm-starting.

Declaration

public void WarmStart(double[] inputs = null, double output = 0)

Parameters

Type	Name	Description
double[]	inputs	not used, leave as null
double	output	not used, leave as null

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test()

Declaration

public string test()

Returns

Type	Description
string

Implements

ISimulatableModel