SI Model Estimation Express VI

Owning Palette: Parametric Model Estimation VIs

Requires: Advanced Signal Processing Toolkit or Control Design and Simulation Module

Estimates the mathematical model for an unknown system.

Details  

Dialog Box Options

Block Diagram Inputs

Block Diagram Outputs

Dialog Box Options

Parameter	Description
Select Model Type	Specifies the type of model to estimate. Contains the following options: AR (autoregressive) ARX (autoregressive with exogenous terms) (default) ARMAX (autoregressive—moving average with exogenous terms) Output-Error Box-Jenkins General-Linear State-Space
Select System Dims	Specifies the dimensions of the system model. Contains the following options: SISO (single-input-single-output) (default) MISO (multiple-input-single-output) MIMO (multiple-input-multiple-output)
Select Data Type	Specifies the data type for the input signal or signals. Contains the following options: Array (default) Waveform
Model Diagram	Displays the mathematical equation for the selected model type and a diagram of the model.
Set Model Orders	Sets the model orders for the selected model type. Note  The options available depend on the model type and system dimensions. Set Model Orders contains the following options: AR order—Specifies the order of the AR model to estimate noise for prewhitening. Method to estimate AR model—Specifies the method to estimate the AR model. Contains the following options: Forward-Backward (default) Least-Squares Yule-Walker Burg-Lattice Principal Component A order—Specifies the order of the A coefficients of the system model. B order—Specifies the order of the B coefficients of the system model. The value of B order must be greater than or equal to 1. Delay—Specifies the delay k of the system model. B orders—Specifies the orders of the B coefficients of the system model. The value of B orders must be greater than or equal to 1. Delays—Specifies the delays k of the system model. A orders—Specifies the orders of the A coefficients of the system model. C order—Specifies the order of the C coefficients of the system model. F order—Specifies the order of the F coefficients of the system model. F orders—Specifies the orders of the F coefficients of the system model. D order—Specifies the order of the D coefficients of the system model. Number of states—Specifies the number of states of the system model.

Block Diagram Inputs

Parameter	Description
stimulus signal	Specifies the input waveform or array of a stimulus signal.
response signal	Specifies the input waveform or array of a response signal.
sampling rate	Specifies the sampling rate for the stimulus signal and response signal.
error in (no error)	Describes error conditions that occur before this node runs.

Block Diagram Outputs

Parameter	Description
system model out	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. Note  You can use a customized system model probe to view model information that flows through system model wires when you debug a block diagram created with the System Identification VIs. Right-click a system model wire and select Custom Probe»SI System Model from the shortcut menu to use the system model probe.
model coefficients	Returns the coefficients of the estimated model system. Note  The elements in model coefficients depend on the model type and the dimensions of the model. model coefficients can contain the following elements: A—Returns the A coefficients of the model for AR, ARX, ARMAX, output-error, Box-Jenkins, and general-linear models and returns the A matrix of state-space models. A has the following characteristics and dimensions: SISO, MISO, and MIMO models—The first value of A always equals 1. The dimension of A equals A order + 1. State-space models—A is an n × n matrix, where n is Number of states. B—Returns the B coefficients of the model for AR, ARX, ARMAX, output-error, Box-Jenkins, and general-linear models, the column vector of the model for state-space SISO models, and the B matrix of the model for state-space MISO and MIMO models. B has the following characteristics and dimensions: SISO models, excluding state-space models—The dimension of B equals B order + Delay. The first Delay number of elements in B always equals 0. MISO and MIMO models, excluding state-space models—The number of rows in B equals the number of system inputs. The number of columns in B equals the maximum value of B orders + Delays. The ith row of B has Delaysi number of zeros at the beginning. State-space SISO models—The dimension of B equals Number of states. State-space MISO and MIMO models—B is an n × m matrix, where n is Number of states and m is the number of system inputs. C—Returns the C coefficients of the model for ARMAX, Box-Jenkins, and general-linear models, the row vector of the model for state-space SISO and MISO models, and the C matrix of the model for state-space MIMO models. C has the following characteristics and dimensions: ARMAX, Box-Jenkins, and general-linear models—The first value of C always equals 1. The dimension of C equals C order + 1. State-space SISO and MISO models—The dimension of C equals Number of states. State-space MIMO models—C is an r × n matrix, where r is the number of system outputs and n is Number of states. D—Returns the D coefficients of the model for Box-Jenkins and general-linear models, the D parameter of the model for state-space SISO models, the row vector of the model for state-space MISO models, and the D matrix of the model for state-space MIMO models. D has the following characteristics and dimensions: Box-Jenkins and general linear models—The first value of D always equals 1. The dimension of D equals D order + 1. State-space MISO models—The dimension of D equals the number of system inputs. State-space MIMO models—D is an r × m matrix, where r is the number of system outputs and m is the number of system inputs. F—Returns the F coefficients of the model for output-error, Box-Jenkins, and general-linear models. F has the following characteristics and dimensions: SISO models—The first value of F always equals 1. The dimension of F equals F order + 1. MISO models—The number of rows in F equals the number of system inputs. The number of columns in F equals the maximum value of F orders + 1.
noise	Returns the disturbance e(t) in the estimated system.
error out	Contains error information. This output provides standard error out functionality.

SI Model Estimation Details

Refer to the LabVIEW System Identification VIs Algorithm References manual for more information about the forward-backward, least-squares, Yule-Walker, Burg-Lattice, and principal component methods.

This Express VI operates similarly to the following VIs and functions:

SI Estimate AR Model
SI Estimate ARX Model
SI Estimate ARMAX Model
SI Estimate OE Model
SI Estimate BJ Model
SI Estimate General Linear Model
SI Estimate State-Space Model