SI Recursively Estimate GL Model VI
Owning Palette: Recursive Model Estimation VIs
Installed With: System Identification Toolkit
Estimates the parameters of a general-linear (GL) model using a recursive method. Wire data to the stimulus signal and response signal inputs to determine the polymorphic instance to use or manually select the instance.
Use the pull-down menu to select an instance of this VI.
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SI Recursively Estimate GL Model (SISO Waveform)
![]() | initialize initializes the internal state of the VI when TRUE. This VI performs calculations that are dependent on all previous data since you last ran the VI or since you set initialize to TRUE. When initialize is TRUE, this VI restarts the calculation dependency. | ||||||||||||
![]() | recursive method specifies the recursive estimation method to use.
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![]() | stimulus signal specifies the input waveform of the stimulus signal. | ||||||||||||
![]() | response signal specifies the input waveform of the response signal. | ||||||||||||
![]() | orders of GL model specifies the orders and delay of the general-linear (GL) model.
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![]() | error in describes error conditions that occur before this VI or function runs.
The default is no error. If an error occurred before this VI or function runs, the VI or function passes the error in value to error out. This VI or function runs normally only if no error occurred before this VI or function runs. If an error occurs while this VI or function runs, it runs normally and sets its own error status in error out. Use the Simple Error Handler or General Error Handler VIs to display the description of the error code. Use error in and error out to check errors and to specify execution order by wiring error out from one node to error in of the next node.
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![]() | ref value specifies the reference value for the recursive estimation algorithms.
When recursive method is KF, ref value is the drift matrix. When recursive method is RLS, this VI uses the value in the first row and the first column of ref value as the forgetting factor. The smaller the forgetting factor, the less information this VI uses from previous estimation calculations. When this VI uses small forgetting factors, the system model is able to track time-varying systems. The range of the forgetting factor is between 0 and 1, typically greater than 0.98 and less than 1. When recursive method is NLMS or LMS, this VI uses the value in the first row and the first column of ref value as the step size. The value of the step size is proportional to the convergence rate. The larger the step size, the faster the convergence. However, the algorithm can become unstable if the step size gets too large. An appropriate step size depends on the model type, order, and input signal. | ||||||||||||
![]() | 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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![]() | predicted response returns the predicted response output from the current estimated system model. The difference between the values of predicted response and response signal is the measure of the recursive estimation. | ||||||||||||
![]() | coefficients of GL model returns the coefficients of the general-linear (GL) model.
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![]() | error out contains error information. If error in indicates that an error occurred before this VI or function ran, error out contains the same error information. Otherwise, it describes the error status that this VI or function produces.
Right-click the error out front panel indicator and select Explain Error from the shortcut menu for more information about the error.
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SI Recursively Estimate GL Model (SISO Array)
![]() | initialize initializes the internal state of the VI when TRUE. This VI performs calculations that are dependent on all previous data since you last ran the VI or since you set initialize to TRUE. When initialize is TRUE, this VI restarts the calculation dependency. | ||||||||||||
![]() | recursive method specifies the recursive estimation method to use.
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![]() | stimulus signal specifies the input array of the stimulus signal. | ||||||||||||
![]() | response signal specifies the input array of the response signal. | ||||||||||||
![]() | orders of GL model specifies the orders and delay of the general-linear (GL) model.
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![]() | error in describes error conditions that occur before this VI or function runs.
The default is no error. If an error occurred before this VI or function runs, the VI or function passes the error in value to error out. This VI or function runs normally only if no error occurred before this VI or function runs. If an error occurs while this VI or function runs, it runs normally and sets its own error status in error out. Use the Simple Error Handler or General Error Handler VIs to display the description of the error code. Use error in and error out to check errors and to specify execution order by wiring error out from one node to error in of the next node.
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![]() | sampling rate is the signal sampling rate in hertz. The value of sampling rate must be greater than 0. | ||||||||||||
![]() | ref value specifies the reference value for the recursive estimation algorithms.
When recursive method is KF, ref value is the drift matrix. When recursive method is RLS, this VI uses the value in the first row and the first column of ref value as the forgetting factor. The smaller the forgetting factor, the less information this VI uses from previous estimation calculations. When this VI uses small forgetting factors, the system model is able to track time-varying systems. The range of the forgetting factor is between 0 and 1, typically greater than 0.98 and less than 1. When recursive method is NLMS or LMS, this VI uses the value in the first row and the first column of ref value as the step size. The value of the step size is proportional to the convergence rate. The larger the step size, the faster the convergence. However, the algorithm can become unstable if the step size gets too large. An appropriate step size depends on the model type, order, and input signal. | ||||||||||||
![]() | 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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![]() | predicted response returns the predicted response output from the current estimated system model. The difference between the values of predicted response and response signal is the measure of the recursive estimation. | ||||||||||||
![]() | coefficients of GL model returns the coefficients of the general-linear (GL) model.
| ||||||||||||
![]() | error out contains error information. If error in indicates that an error occurred before this VI or function ran, error out contains the same error information. Otherwise, it describes the error status that this VI or function produces.
Right-click the error out front panel indicator and select Explain Error from the shortcut menu for more information about the error.
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SI Recursively Estimate GL Model (MISO Waveform)
![]() | initialize initializes the internal state of the VI when TRUE. This VI performs calculations that are dependent on all previous data since you last ran the VI or since you set initialize to TRUE. When initialize is TRUE, this VI restarts the calculation dependency. | ||||||||||||
![]() | recursive method specifies the recursive estimation method to use.
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![]() | stimulus signals specifies the input waveform array of the stimulus signals. Each element of the array is the waveform of one stimulus signal. | ||||||||||||
![]() | response signal specifies the input waveform of the response signal. | ||||||||||||
![]() | orders of GL model specifies the orders and delays of the general-linear (GL) model.
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![]() | error in describes error conditions that occur before this VI or function runs.
The default is no error. If an error occurred before this VI or function runs, the VI or function passes the error in value to error out. This VI or function runs normally only if no error occurred before this VI or function runs. If an error occurs while this VI or function runs, it runs normally and sets its own error status in error out. Use the Simple Error Handler or General Error Handler VIs to display the description of the error code. Use error in and error out to check errors and to specify execution order by wiring error out from one node to error in of the next node.
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![]() | ref value specifies the reference value for the recursive estimation algorithms.
When recursive method is KF, ref value is the drift matrix. When recursive method is RLS, this VI uses the value in the first row and the first column of ref value as the forgetting factor. The smaller the forgetting factor, the less information this VI uses from previous estimation calculations. When this VI uses small forgetting factors, the system model is able to track time-varying systems. The range of the forgetting factor is between 0 and 1, typically greater than 0.98 and less than 1. When recursive method is NLMS or LMS, this VI uses the value in the first row and the first column of ref value as the step size. The value of the step size is proportional to the convergence rate. The larger the step size, the faster the convergence. However, the algorithm can become unstable if the step size gets too large. An appropriate step size depends on the model type, order, and input signal. | ||||||||||||
![]() | 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.
| ||||||||||||
![]() | predicted response returns the predicted response output from the current estimated system model. The difference between the values of predicted response and response signal is the measure of the recursive estimation. | ||||||||||||
![]() | coefficients of GL model returns the coefficients of the general-linear (GL) model.
| ||||||||||||
![]() | error out contains error information. If error in indicates that an error occurred before this VI or function ran, error out contains the same error information. Otherwise, it describes the error status that this VI or function produces.
Right-click the error out front panel indicator and select Explain Error from the shortcut menu for more information about the error.
|
SI Recursively Estimate GL Model (MISO Array)
![]() | initialize initializes the internal state of the VI when TRUE. This VI performs calculations that are dependent on all previous data since you last ran the VI or since you set initialize to TRUE. When initialize is TRUE, this VI restarts the calculation dependency. | ||||||||||||
![]() | recursive method specifies the recursive estimation method to use.
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![]() | stimulus signals specifies the input array of the stimulus signals. Each row in the array is one stimulus signal. | ||||||||||||
![]() | response signal specifies the input array of the response signal. | ||||||||||||
![]() | orders of GL model specifies the orders and delays of the general-linear (GL) model.
| ||||||||||||
![]() | error in describes error conditions that occur before this VI or function runs.
The default is no error. If an error occurred before this VI or function runs, the VI or function passes the error in value to error out. This VI or function runs normally only if no error occurred before this VI or function runs. If an error occurs while this VI or function runs, it runs normally and sets its own error status in error out. Use the Simple Error Handler or General Error Handler VIs to display the description of the error code. Use error in and error out to check errors and to specify execution order by wiring error out from one node to error in of the next node.
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![]() | sampling rate is the signal sampling rate in hertz. The value of sampling rate must be greater than 0. | ||||||||||||
![]() | ref value specifies the reference value for the recursive estimation algorithms.
When recursive method is KF, ref value is the drift matrix. When recursive method is RLS, this VI uses the value in the first row and the first column of ref value as the forgetting factor. The smaller the forgetting factor, the less information this VI uses from previous estimation calculations. When this VI uses small forgetting factors, the system model is able to track time-varying systems. The range of the forgetting factor is between 0 and 1, typically greater than 0.98 and less than 1. When recursive method is NLMS or LMS, this VI uses the value in the first row and the first column of ref value as the step size. The value of the step size is proportional to the convergence rate. The larger the step size, the faster the convergence. However, the algorithm can become unstable if the step size gets too large. An appropriate step size depends on the model type, order, and input signal. | ||||||||||||
![]() | 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.
| ||||||||||||
![]() | predicted response returns the predicted response output from the current estimated system model. The difference between the values of predicted response and response signal is the measure of the recursive estimation. | ||||||||||||
![]() | coefficients of GL model returns the coefficients of the general-linear (GL) model.
| ||||||||||||
![]() | error out contains error information. If error in indicates that an error occurred before this VI or function ran, error out contains the same error information. Otherwise, it describes the error status that this VI or function produces.
Right-click the error out front panel indicator and select Explain Error from the shortcut menu for more information about the error.
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Example
Refer to the Online Model Estimation VI in the labview\examples\System Identification\Getting Started\Recursive Estimation.llb for an example of using the SI Recursively Estimate GL Model VI.