System Identification VIs
June 2008, 370805D-01
Installed With: System Identification Toolkit. This topic might not match its corresponding palette in LabVIEW depending on your operating system, licensed product(s), and target.
Use the System Identification VIs to create and estimate mathematical models of dynamic systems. You can use the VIs to estimate accurate models of systems based on observed input-output data.
The VIs on this palette can return general LabVIEW error codes or specific system identification error codes.
| Subpalette | Description |
|---|---|
| Data Preprocessing VIs | Use the Data Preprocessing VIs to preprocess the raw data that you acquired from an unknown system. |
| Frequency-Domain Model Estimation VIs | Use the Frequency-Domain Model Estimation VIs to estimate the frequency response function (FRF) and to identify a transfer function (TF) or a state-space (SS) model of an unknown system. |
| Model Analysis VIs | Use the Model Analysis VIs to perform a Bode, Nyquist, or pole-zero analysis of a system model and to compute the standard deviation of the results. |
| Model Conversion VIs | Use the Model Conversion VIs to convert models created in the LabVIEW System Identification Toolkit into models you can use with the LabVIEW Control Design and Simulation Module. You can convert an AR, ARX, ARMAX, output-error, Box-Jenkins, general-linear, or state-space model into a transfer function, zero-pole-gain, or state-space model. You also can convert a continuous model to a discrete model or convert a discrete model to a continuous model. |
| Model Management VIs | Use the Model Management VIs to access information about the system model. Model information includes properties such as the system type, sampling rate, system dimensions, noise covariance, and so on. |
| Model Validation VIs | Use the Model Validation VIs to analyze and validate a system model. |
| Nonparametric Model Estimation VIs | Use the Nonparametric Model Estimation VIs to estimate the impulse response or frequency response of an unknown, linear, time-invariant system from an input and corresponding output signal. |
| Parametric Model Estimation VIs | Use the Parametric Model Estimation VIs to estimate a parametric mathematical model for an unknown, linear, time-invariant system. |
| Partially Known Model Estimation VIs | Use the Partially Known Model Estimation VIs to create and estimate partially known models for the plant in a system. |
| Recursive Model Estimation VIs | Use the Recursive Model Estimation VIs to recursively estimate the parametric mathematical model for an unknown system. |
| Utilities VIs | Use the Utilities VIs to perform miscellaneous tasks on data or the system model, including producing data samples, displaying model equations, merging models, and so on. |
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