SI Estimate Partially Known State-Space Model VI
- Updated2023-03-14
- 16 minute(s) read
SI Estimate Partially Known State-Space Model VI
Owning Palette: Partially Known Model Estimation VIs
Requires: Advanced Signal Processing Toolkit or Control Design and Simulation Module
Estimates a state-space model for a partially known system. Use the SI Create Partially Known State-Space Model VI to create the model you want to estimate. Wire data to the stimulus signal and response signal inputs to determine the polymorphic instance to use or manually select the instance.
SI Estimate Partially Known State-Space Model (SISO Waveform)

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system model in contains information for the mathematical model of a partially known system. The information includes the model type, model orders, constraints on each of the model coefficients, input and output names of the system, and so on. | ||||||||
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stimulus signal specifies the input waveform of the stimulus signal. | ||||||||
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response signal specifies the input waveform of the response signal. | ||||||||
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error in describes error conditions that occur before this node runs. This input provides standard error in functionality. | ||||||||
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Kalman gain returns the Kalman gain of the state-space model. | ||||||||
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system model out returns information about the model structure, nominal or estimated parameters, identification result, and so on. Use the Model Management VIs to retrieve the information system model out contains.
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coefficients of state-space model returns the coefficients of the state-space model.
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variables returns the names and values of the variables in the state-space model.
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error out contains error information. This output provides standard error out functionality. | ||||||||
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initial states returns the initial states of the state-space model. |
SI Estimate Partially Known State-Space Model (SISO Array)

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system model in contains information for the mathematical model of a partially known system. The information includes the model type, model orders, constraints on each of the model coefficients, input and output names of the system, and so on. | ||||||||
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stimulus signal specifies an array that represents the stimulus signal. | ||||||||
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response signal specifies an array that represents the response signal. | ||||||||
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error in describes error conditions that occur before this node runs. This input provides standard error in functionality. | ||||||||
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sampling rate (Hz) specifies the sampling frequency in hertz. For continuous models, sampling rate is used to convert the continuous system to a discrete system before this VI simulates the output. For discrete models, sampling rate is the sampling rate of the system. | ||||||||
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Kalman gain returns the Kalman gain of the state-space model. | ||||||||
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system model out returns information about the model structure, nominal or estimated parameters, identification result, and so on. Use the Model Management VIs to retrieve the information system model out contains.
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coefficients of state-space model returns the coefficients of the state-space model.
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variables returns the names and values of the variables in the state-space model.
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error out contains error information. This output provides standard error out functionality. | ||||||||
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initial states returns the initial states of the state-space model. |
SI Estimate Partially Known State-Space Model (MISO Waveform)

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system model in contains information for the mathematical model of a partially known system. The information includes the model type, model orders, constraints on each of the model coefficients, input and output names of the system, and so on. | ||||||||
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stimulus signals specifies the input waveform of the stimulus signals. Each element of the waveform array is the waveform of one stimulus signal. | ||||||||
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response signal specifies the input waveform of the response signal. | ||||||||
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error in describes error conditions that occur before this node runs. This input provides standard error in functionality. | ||||||||
![]() |
Kalman gain returns the Kalman gain of the state-space model. | ||||||||
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system model out returns information about the model structure, nominal or estimated parameters, identification result, and so on. Use the Model Management VIs to retrieve the information system model out contains.
|
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coefficients of state-space model returns the coefficients of the state-space model.
| ||||||||
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variables returns the names and values of the variables in the state-space model.
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error out contains error information. This output provides standard error out functionality. | ||||||||
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initial states returns the initial states of the state-space model. |
SI Estimate Partially Known State-Space Model (MISO Array)

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system model in contains information for the mathematical model of a partially known system. The information includes the model type, model orders, constraints on each of the model coefficients, input and output names of the system, and so on. | ||||||||
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stimulus signals specifies an array that represents the stimulus signals. Each element in the array is one stimulus signal. | ||||||||
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response signal specifies an array that represents the response signal. | ||||||||
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error in describes error conditions that occur before this node runs. This input provides standard error in functionality. | ||||||||
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sampling rate (Hz) specifies the sampling frequency in hertz. For continuous models, sampling rate is used to convert the continuous system to a discrete system before this VI simulates the output. For discrete models, sampling rate is the sampling rate of the system. | ||||||||
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Kalman gain returns the Kalman gain of the state-space model. | ||||||||
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system model out returns information about the model structure, nominal or estimated parameters, identification result, and so on. Use the Model Management VIs to retrieve the information system model out contains.
|
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coefficients of state-space model returns the coefficients of the state-space model.
| ||||||||
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variables returns the names and values of the variables in the state-space model.
| ||||||||
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error out contains error information. This output provides standard error out functionality. | ||||||||
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initial states returns the initial states of the state-space model. |
SI Estimate Partially Known State-Space Model (MIMO Waveform)

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system model in contains information for the mathematical model of a partially known system. The information includes the model type, model orders, constraints on each of the model coefficients, input and output names of the system, and so on. | ||||||||
![]() |
stimulus signals specifies the input waveform of the stimulus signals. Each element of the waveform array is the waveform of one stimulus signal. | ||||||||
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response signals specifies the input waveform array of the response signals. Each element of the array is the waveform of one response signal. | ||||||||
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error in describes error conditions that occur before this node runs. This input provides standard error in functionality. | ||||||||
![]() |
Kalman gain returns the Kalman gain of the state-space model. | ||||||||
![]() |
system model out returns information about the model structure, nominal or estimated parameters, identification result, and so on. Use the Model Management VIs to retrieve the information system model out contains.
|
||||||||
![]() |
coefficients of state-space model returns the coefficients of the state-space model.
| ||||||||
![]() |
variables returns the names and values of the variables in the state-space model.
| ||||||||
![]() |
error out contains error information. This output provides standard error out functionality. | ||||||||
![]() |
initial states returns the initial states of the state-space model. |
SI Estimate Partially Known State-Space Model (MIMO Array)

![]() |
system model in contains information for the mathematical model of a partially known system. The information includes the model type, model orders, constraints on each of the model coefficients, input and output names of the system, and so on. | ||||||||
![]() |
stimulus signals specifies an array that represents the stimulus signals. Each element in the array is one stimulus signal. | ||||||||
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response signals specifies an array that represents the response signals. Each element in the array is one response signal. | ||||||||
![]() |
error in describes error conditions that occur before this node runs. This input provides standard error in functionality. | ||||||||
![]() |
sampling rate (Hz) specifies the sampling frequency in hertz. For continuous models, sampling rate is used to convert the continuous system to a discrete system before this VI simulates the output. For discrete models, sampling rate is the sampling rate of the system. | ||||||||
![]() |
Kalman gain returns the Kalman gain of the state-space model. | ||||||||
![]() |
system model out returns information about the model structure, nominal or estimated parameters, identification result, and so on. Use the Model Management VIs to retrieve the information system model out contains.
|
||||||||
![]() |
coefficients of state-space model returns the coefficients of the state-space model.
| ||||||||
![]() |
variables returns the names and values of the variables in the state-space model.
| ||||||||
![]() |
error out contains error information. This output provides standard error out functionality. | ||||||||
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initial states returns the initial states of the state-space model. |
SI Estimate Partially Known State-Space Model Details
The SI Estimate Partially Known State-Space Model VI estimates a continuous or discrete state-space model for a partially known system, depending on the system model input. This VI accepts only models theSI Create Partially Known State-Space Model VI creates. When estimating discrete models from array data, you must set sampling rate to the same sampling rate you set when you created the model using the SI Create Partially Known State-Space Model VI. When estimating continuous models from array data, you must set the sampling rate for the VI to convert continuous systems to discrete systems. This VI simulates the output and then compares the simulated output with the response signal to optimize estimation.
Examples
Refer to the following VIs for examples of using the SI Estimate Partially Known State-Space Model VI:
- Continuous State-Space Model of an RLC Circuit VI: labview\examples\System Identification\Getting Started\Grey-Box Model.llb
- Belt-driven Motion System (Greybox) VI: labview\examples\System Identification\Industry Applications\Mechanical Systems.llb













