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Simulation and Prediction

Simulate or predict response of identified models; import identified models in Simulink® using model simulation blocks

You can simulate the response of an identified model to given inputs in the System Identification app and using sim. You can predict the model response a certain time horizon into the future using past measurements of inputs and outputs. Use predict to predict model response over the time span of the measured data, and use forecast to predict the response over a future time span when no measured data is available. You can also import identified models to Simulink, and simulate model response using model simulation blocks.

Functions

simSimulate response of identified model
simOptionsOption set for sim
simsdSimulate linear models with uncertainty using Monte Carlo method
simsdOptionsOption set for simsd
predictPredict K-step ahead model output
predictOptionsOption set for predict
forecastForecast identified model output
forecastOptionsOption set for forecast
idinputGenerate input signals

Blocks

Iddata SourceImport time-domain data stored in iddata object in MATLAB workspace
Iddata SinkExport simulation data as iddata object to MATLAB workspace
IdmodelSimulate identified linear model in Simulink software
Nonlinear ARX ModelSimulate nonlinear ARX model in Simulink software
Hammerstein-Wiener ModelSimulate Hammerstein-Wiener model in Simulink software
Nonlinear Grey-Box ModelSimulate nonlinear grey-box model in Simulink software

Topics

Simulation and Prediction

Simulating and Predicting Model Output

You primarily use a model is to simulate its output, i.e., calculate the output (y(t)) for given input values.

Simulation and Prediction in the App

Perform simulation and prediction in the System Identification app, and interpret results.

Simulation and Prediction at the Command Line

Perform simulation, prediction, and forecasting at the command line, specify initial conditions.

Simulating Identified Model Output in Simulink

Blocks for importing and simulating models from the MATLAB® environment into a Simulink model.

Using System Identification Toolbox Blocks in Simulink Models

Description of the System Identification Toolbox™ block library.

Forecasting

Introduction to Forecasting of Dynamic System Response

Understand the concept of forecasting data using linear and nonlinear models.

Forecast the Output of a Dynamic System

Workflow for forecasting time series data and input-output data using linear and nonlinear models.

Perform Multivariate Time Series Forecasting

This example shows how to perform multivariate time series forecasting of data measured from predator and prey populations in a prey crowding scenario.

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