仿真与预测

仿真或预测辨识模型的响应；使用模型仿真模块在 Simulink^® 中导入辨识模型

您可以在系统辨识中使用 sim 仿真辨识模型对给定输入的响应。您可以使用过去的输入和输出测量值来预测模型在未来某个时间范围内的响应。使用 predict 可预测模型在测量数据时间范围内的响应，使用 forecast 可在没有测量数据的情况下预测模型在未来时间范围内的响应。您还可以将辨识模型导入 Simulink，并使用模型仿真模块对模型响应进行仿真。

函数

`sim`	Simulate response of identified model
`simOptions`	Option set for `sim`
`simsd`	Simulate linear models with uncertainty using Monte Carlo method
`simsdOptions`	Option set for `simsd`
`predict`	预测辨识模型的 K 步输出
`predictOptions`	Option set for `predict`
`forecast`	Forecast time-series values into future
`forecastOptions`	Option set for `forecast`
`idinput`	生成输入信号以支持系统辨识

模块

Iddata Source	导入存储在 MATLAB 工作区中 `iddata` 对象内的时域数据
Iddata Sink	将仿真数据作为 `iddata` 对象导出到 MATLAB 工作区
Idmodel	Simulate identified linear model in Simulink software
Nonlinear ARX Model	在 Simulink 软件中仿真非线性 ARX 模型
Hammerstein-Wiener Model	在 Simulink 软件中仿真哈默斯坦-维纳模型
Nonlinear Grey-Box Model	在 Simulink 软件中仿真非线性灰盒模型

主题

仿真与预测

Simulate and Predict Identified Model Output
Understand the difference between simulated and predicted output and when to use each.
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.
Simulate Identified Model in Simulink
Use model blocks to import, initialize, and simulate models from the MATLAB^® environment into a Simulink model.

预测

Introduction to Forecasting of Dynamic System Response
Understand the concept of forecasting data using linear and nonlinear models.
Forecast Output of Dynamic System
Workflow for forecasting time series data and input-output data using linear and nonlinear models.
Forecast Multivariate Time Series
This example shows how to perform multivariate time series forecasting of data measured from predator and prey populations in a prey crowding scenario.