System Identification Toolbox - Documentation

Contents

Index

• Getting Started

• Choosing Your System Identification Strategy

Recommended Model Estimation Sequence

• Supported Models for Time- and Frequency-Domain Data

Supported Models for Time-Domain Data

Supported Models for Frequency-Domain Data

Supported Continuous-Time and Discrete-Time Models

Commands for Model Estimation

• Creating Model Structures at the Command Line

About System Identification Toolbox Model Objects

When to Construct a Model Structure Independently of Estimation

Commands for Constructing Model Structures

Model Properties

• Modeling Multiple-Output Systems

About Modeling Multiple-Output Systems

Modeling Multiple Outputs Directly

Modeling Multiple Outputs as a Combination of Single-Output Models

Improving Multiple-Output Estimation Results by Weighing Outputs During Estimation

• Data Import and Processing

Types of Data You Can Model

Ways to Process Data for System Identification

Requirements on Data Sampling

• Importing Data into the MATLAB Workspace

Importing Time-Domain Data into MATLAB

Importing Time-Series Data into MATLAB

Importing Frequency-Domain Data into MATLAB

Importing Frequency-Response Data into MATLAB

• Importing Data into the GUI

Types of Data You Can Import into the GUI

Importing Time-Domain Data into the GUI

Importing Frequency-Domain Data into the GUI

Importing Frequency-Response Data into the GUI

Importing Data Objects into the GUI

Specifying the Data Sampling Interval

Specifying Estimation and Validation Data

Preprocessing Data Using Quick Start

Creating Data Sets from a Subset of Signal Channels

Creating Multiexperiment Data Sets in the GUI

Viewing Data Properties

Renaming Data and Changing Display Color

Distinguishing Data Types in the GUI

Organizing Data Icons

Deleting Data Sets in the GUI

Exporting Data from the GUI to the MATLAB Workspace

• Representing Time- and Frequency-Domain Data Using iddata Objects

iddata Constructor

iddata Properties

Creating Multiexperiment Data at the Command Line

Subreferencing iddata Objects

Modifying Time and Frequency Vectors

Naming, Adding, and Removing Data Channels

Concatenating iddata Objects

• Representing Frequency-Response Data Using idfrd Objects

idfrd Constructor

idfrd Properties

Subreferencing idfrd Objects

Concatenating idfrd Objects

• Analyzing Data Quality

Is Your Data Ready for Modeling?

Plotting Data in the GUI Versus at the Command Line

How to Plot Data in the GUI

How to Plot Data at the Command Line

How to Analyze Data Using the advice Command

• Selecting Subsets of Data

Why Select Subsets of Data?

Selecting Data Using the GUI

Selecting Data at the Command Line

• Handling Missing Data and Outliers

Handling Missing Data

Handling Outliers

Example - Extracting and Modeling Specific Data Segments

• Handling Offsets and Trends in Data

When to Detrend Data

Alternatives for Detrending Data in GUI or at the Command-Line

How to Detrend Data Using the GUI

How to Detrend Data at the Command Line

Next Steps After Detrending

• Resampling Data

What Is Resampling?

Resampling Data Using the GUI

Resampling Data at the Command Line

Resampling Data Without Aliasing Effects

• Filtering Data

Supported Filters

Choosing to Prefilter Your Data

How to Filter Data Using the GUI

How to Filter Data at the Command Line

• Generating Data Using Simulation

Commands for Generating and Simulating Data

Example - Creating Data with Periodic Inputs

Example - Generating Data Using Simulation

Simulating Data Using Other MathWorks Products

• Transforming Between Time- and Frequency-Domain Data

Transforming Data Domain in the GUI

Transforming Data Domain at the Command Line

• Manipulating Complex-Valued Data

Supported Operations for Complex Data

Processing Complex iddata Signals at the Command Line

• Linear Model Identification

• Identifying Frequency-Response Models

What Is a Frequency-Response Model?

Data Supported by Frequency-Response Models

How to Estimate Frequency-Response Models in the GUI

How to Estimate Frequency-Response Models at the Command Line

Options for Computing Spectral Models

Options for Frequency Resolution

Spectrum Normalization

• Identifying Impulse-Response Models

What Is Time-Domain Correlation Analysis?

Data Supported by Correlation Analysis

How to Estimate Impulse and Step Response Models Using the GUI

How to Estimate Impulse and Step Response Models at the Command Line

How to Compute Response Values

How to Identify Delay Using Transient-Response Plots

Algorithm for Correlation Analysis

• Identifying Low-Order Transfer Functions (Process Models)

What Is a Process Model?

Data Supported by a Process Model

How to Estimate Process Models Using the GUI

How to Estimate Process Models at the Command Line

Options for Specifying the Process-Model Structure

Options for Multiple-Input Models

Options for the Disturbance Model Structure

Options for Frequency-Weighing Focus

Options for Initial States

• Identifying Input-Output Polynomial Models

What Are Black-Box Polynomial Models?

Data Supported by Polynomial Models

Preliminary Step - Estimating Model Orders and Input Delays

How to Estimate Polynomial Models in the GUI

How to Estimate Polynomial Models at the Command Line

Options for Multiple-Input and Multiple-Output ARX Orders

Option for Frequency-Weighing Focus

Options for Initial States

Algorithms for Estimating Polynomial Models

Example - Estimating Models Using armax

• Identifying State-Space Models

What Are State-Space Models?

Data Supported by State-Space Models

Supported State-Space Parameterizations

Preliminary Step - Estimating State-Space Model Orders

How to Estimate State-Space Models in the GUI

How to Estimate State-Space Models at the Command Line

How to Estimate Free-Parameterization State-Space Models

How to Estimate State-Space Models with Canonical Parameterization

How to Estimate State-Space Models with Structured Parameterization

How to Estimate the State-Space Equivalent of ARMAX and OE Models

Options for Frequency-Weighing Focus

Options for Initial States

Algorithms for Estimating State-Space Models

• Refining Linear Parametric Models

When to Refine Models

What You Specify to Refine a Model

How to Refine Linear Parametric Models in the GUI

How to Refine Linear Parametric Models at the Command Line

Extracting Parameter Values from Linear Models

Extracting Dynamic Model and Noise Model Separately

• Transforming Between Discrete-Time and Continuous-Time Representations

Why Transform Between Continuous and Discrete Time?

Using the c2d, d2c, and d2d Commands

Specifying Intersample Behavior

How d2c Handles Input Delays

Effects on the Noise Model

Transforming Between Linear Model Representations

• Subreferencing Model Objects

What Is Subreferencing?

Limitation on Supported Models

Subreferencing Specific Measured Channels

Subreferencing Measured and Noise Models

Treating Noise Channels as Measured Inputs

• Concatenating Model Objects

About Concatenating Models

Limitation on Supported Models

Horizontal Concatenation of Model Objects

Vertical Concatenation of Model Objects

Concatenating Noise Spectrum Data of idfrd Objects

Merging Model Objects

• Nonlinear Black-Box Model Identification

• About Nonlinear Model Identification

What Are Nonlinear Models?

When to Fit Nonlinear Models

Available Nonlinear Models

Preparing Data for Nonlinear Identification

• Identifying Nonlinear ARX Models

Nonlinear ARX Model Extends the Linear ARX Structure

Structure of Nonlinear ARX Models

Nonlinearity Estimators for Nonlinear ARX Models

Ways to Configure Nonlinear ARX Estimation

How to Estimate Nonlinear ARX Models in the GUI

How to Estimate Nonlinear ARX Models at the Command Line

Using Nonlinear ARX Models

Low-Level Manipulation of Nonlinear ARX Components

• Identifying Hammerstein-Wiener Models

Applications of Hammerstein-Wiener Models

Structure of Hammerstein-Wiener Models

Nonlinearity Estimators for Hammerstein-Wiener Models

Ways to Configure Hammerstein-Wiener Estimation

Estimation Algorithm for Hammerstein-Wiener Models

How to Estimate Hammerstein-Wiener Models in the GUI

How to Estimate Hammerstein-Wiener Models at the Command Line

Using Hammerstein-Wiener Models

Low-Level Manipulation of Hammerstein-Wiener Components

• Linear Approximation of Nonlinear Black-Box Models

Why Compute a Linear Approximation of a Nonlinear Model?

Choosing Your Linear Approximation Approach

Linear Approximation of Nonlinear Black-Box Models for a Given Input

Tangent Linearization of Nonlinear Black-Box Models

Computing Operating Points for Nonlinear Black-Box Models

• ODE Parameter Estimation (Grey-Box Modeling)

Supported Grey-Box Models

Data Supported by Grey-Box Models

Choosing idgrey or idnlgrey Model Object

• Estimating Linear Grey-Box Models

Specifying the Linear Grey-Box Model Structure

Example - Representing a Grey-Box Model in an M-File

Example - Estimating a Continuous-Time Grey-Box Model for Heat Diffusion

Example - Estimating a Discrete-Time Grey-Box Model with Parameterized Disturbance

• Estimating Nonlinear Grey-Box Models

Supported Nonlinear Grey-Box Models

Nonlinear Grey-Box Demos and Examples

Specifying the Nonlinear Grey-Box Model Structure

Constructing the idnlgrey Object

Using pem to Estimate Nonlinear Grey-Box Models

Options for the Estimation Algorithm

After Estimating Grey-Box Models

• Time Series Model Identification

What Are Time-Series Models?

Preparing Time-Series Data

• Estimating Time-Series Power Spectra

How to Estimate Time-Series Power Spectra Using the GUI

How to Estimate Time-Series Power Spectra at the Command Line

• Estimating AR and ARMA Models

Definition of AR and ARMA Models

Estimating Polynomial Time-Series Models in the GUI

Estimating AR and ARMA Models at the Command Line

• Estimating State-Space Time-Series Models

Definition of State-Space Time-Series Model

Estimating State-Space Models at the Command Line

Example - Identifying Time-Series Models at the Command Line

Estimating Nonlinear Models for Time-Series Data

• Recursive Techniques for Model Identification

What Is Recursive Estimation?

Commands for Recursive Estimation

• Algorithms for Recursive Estimation

Types of Recursive Estimation Algorithms

General Form of Recursive Estimation Algorithm

Kalman Filter Algorithm

Forgetting Factor Algorithm

Unnormalized and Normalized Gradient Algorithms

Data Segmentation

• Model Analysis

• Overview of Model Validation and Plots

When to Validate Models

Ways to Validate Models

Data for Validating Models

Supported Model Plots

Plotting Models in the GUI

Getting Advice About Models

• Simulating and Predicting Model Output

Choosing to Simulate or Predict Model Output

Simulation and Prediction in the GUI

Simulation and Prediction at the Command Line

• Residual Analysis

What Is Residual Analysis?

Supported Model Types

What Residual Plots Show for Different Data Domains

Displaying the Confidence Interval

How to Plot Residuals Using the GUI

How to Plot Residuals at the Command Line

Example - Examining Model Residuals

• Impulse and Step Response Plots

Supported Models

How Transient Response Helps to Validate Models

What Does a Transient Response Plot Show?

How to Plot Impulse and Step Response Using the GUI

Displaying the Confidence Interval

How to Plot Impulse and Step Response at the Command Line

• Frequency Response Plots

What Is Frequency Response?

How Frequency Response Helps to Validate Models

What Does a Frequency-Response Plot Show?

How to Plot Bode Plots Using the GUI

How to Plot Bode and Nyquist Plots at the Command Line

• Noise Spectrum Plots

Supported Models

What Does a Noise Spectrum Plot Show?

Displaying the Confidence Interval

How to Plot the Noise Spectrum Using the GUI

How to Plot the Noise Spectrum at the Command Line

• Pole and Zero Plots

Supported Models

What Does a Pole-Zero Plot Show?

How to Plot Model Poles and Zeros Using the GUI

How to Plot Poles and Zeros at the Command Line

Reducing Model Order Using Pole-Zero Plots

• Nonlinear ARX Model Plots

About Nonlinear ARX Plots

How to Plot Nonlinear ARX Plots Using the GUI

Configuring the Nonlinear ARX Plot

Axis Limits, Legend, and 3-D Rotation

How to Plot Nonlinear ARX Plots at the Command Line

• Hammerstein-Wiener Model Plots

About Hammerstein-Wiener Plots

How to Create Hammerstein-Wiener Plots in the GUI

How to Plot Hammerstein-Wiener Plots at the Command Line

Plotting Nonlinear Block Characteristics

Plotting Linear Block Characteristics

• Akaike's Criteria for Model Validation

Definition of FPE

Definition of AIC

• Computing Model Uncertainty

Why Analyze Model Uncertainty?

What Is Model Covariance?

Viewing Model Uncertainty Information

• Troubleshooting Models

About Troubleshooting Models

Model Order Is Too High or Too Low

Nonlinearity Estimator Produces a Poor Fit

Substantial Noise in the System

Unstable Models

Missing Input Variables

Complicated Nonlinearities

Next Steps After Getting an Accurate Model

• Using Identified Models in Control Design

• Using Models with Control System Toolbox Software

How Control System Toolbox Software Works with Identified Models

Using balred to Reduce Model Order

Compensator Design Using Control System Toolbox Software

Converting Models to LTI Objects

Viewing Model Response Using the LTI Viewer

Combining Model Objects

Example - Using System Identification Toolbox Software with Control System Toolbox Software

• Using System Identification Toolbox Blocks

System Identification Toolbox Block Library

Opening the System Identification Toolbox Block Library

Identifying Linear Models

• Simulating Model Output

When to Use Simulation Blocks

Summary of Simulation Blocks

Specifying Initial Conditions for Simulation

Example - Simulating a Model Using Simulink Software

• Using the System Identification Tool GUI

Steps for Using the System Identification Tool GUI

• Starting and Managing GUI Sessions

What Is a System Identification Tool Session?

Starting a New Session in the GUI

Description of the System Identification Tool Window

Opening a Saved Session

Saving, Merging, and Closing Sessions

Deleting a Session

Getting Help in the GUI

Exiting the System Identification Tool GUI

• Managing Models in the GUI

Importing Models into the GUI

Viewing Model Properties

Renaming Models and Changing Display Color

Organizing Model Icons

Deleting Models in the GUI

Exporting Models from the GUI to the MATLAB Workspace

• Working with Plots in the System Identification Tool GUI

Identifying Data Sets and Models on Plots

Changing and Restoring Default Axis Limits

Selecting Measured and Noise Channels in Plots

Grid and Line Styles in Plots

Opening a Plot in a MATLAB Figure Window

• Customizing the System Identification Tool GUI

Types of GUI Customization

Displaying Warnings While You Work

Saving Session Preferences

Modifying idlayout.m

• Release Notes

System Identification Toolbox roadmap
page

	Functions:
	By Category
	Alphabetical List

	Blocks:
	By Category
	Alphabetical List



	Documentation Set

	Getting Started
	Introduces System Identification Toolbox software and gets you started using it

	User's Guide
	Provides comprehensive information about System Identification Toolbox software

	Examples in Documentation
	Lists major examples in the System Identification Toolbox documentation



	Product Demos

	System Identification Toolbox Demos
	Presents a collection of demos that you can run from the Help browser to help you learn the product



	What's New

	Release Notes
	Summarizes new features, bug fixes, upgrade issues, etc.



	Printable (PDF) Documentation on the Web

PDF documents reflect the most recent version of System Identification Toolbox and might describe features not available in earlier versions of the software.
	System Identification Toolbox Getting Started Guide
	System Identification Toolbox User's Guide
	System Identification Toolbox Reference
	System Identification Toolbox Release Notes

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