System Identification Toolbox

Specialized Tools for Identifying First-, Second-, and Third-Order Dynamic Models  

This video demo provides an overview of a specialized graphical user interface(GUI) in the System Identification Toolbox for modeling lower-order, continuous dynamic systems from data.

Parametric Model Estimation  

This video demonstration provides an overview of the System Identification Toolbox and shows how to estimate a linear model of a dynamic system using the product's graphical user interface.

Estimating Simple Models from Real Laboratory Process Data  

In this demo we show how System Identification Toolbox can be used to develop and analyze simple models from a real laboratory process data.

A Vehicle Dynamics System  

In this demo we will estimate the longitudinal and the lateral stiffness of a tire using so-called bicycle vehicle model.

Glass Tube Manufacturing Process  

This case study describes linear model identification for a glass tube manufacturing process.

An Industrial Robot Arm  

This demo shows how to create a nonlinear grey-box model of an industrial robot arm from measured input-output data.

Nonlinear Modeling of a Magneto-Rheological Fluid Damper  

This demo shows how you can create nonlinear ARX and Hammerstein-Wiener models of the magneto-rheological fluid damper using measurements of its velocity and the damping force.

Modeling an Aerodynamic Body  

This case study demonstrates nonlinear grey-box modeling ability of System Identification Toolbox to estimate a large number of parameters in a multi-input multi-output guided missile system.

Modeling Current Signal From an Energizing Transformer  

This case study shows how System Identification Toolbox can be used for describing dynamic characteristics of a signal and predicting its future values from a measurement of the past values.

Estimating Continuous-Time Models using Simulink^® Data  

This demo illustrates how models simulated in Simulink^® can be identified using System Identification Toolbox.

Data and Model Objects in System Identification Toolbox™  

This demonstration shows how to create and work with data and model objects in System Identification Toolbox.

Building and Estimating Process Models Using System Identification Toolbox™  

This demo describes how to build simple process models using System Identification Toolbox.

Frequency Domain Identification: Estimating Models Using Frequency Domain Data  

This demo illustrates the use of frequency domain data in System Identification Toolbox.

Model Structure Selection: Determining Model Order and Input Delay  

This demo describes some of the options in System Identification Toolbox for determining model order and input delay.

A Comparison of Various Model Identification Methods  

In this demo we compare SPA, PEM, ARX, OE, ARMAX and BJ - several of the identification methods that are provided by System Identification Toolbox.

Dealing with Multi-Variable Systems: Identification and Analysis  

This demo shows how to deal with data with several input and output channels (MIMO data).

Building Structured and User-Defined Models Using System Identification Toolbox™  

In this demo we will demonstrate how to use utilities in System Identification Toolbox to estimate parameters in user-defined model structures, such as IDPROC and IDGREY.

Spectrum Estimation using Complex Data - Marple's Test Case  

In this demo we consider spectrum estimation using Marple's test case.

Recursive Estimation and Data Segmentation Techniques in System Identification Toolbox™  

This demo describes a group of recursive ("online") algorithms in the System Identification Toolbox. We also discuss data segmentation as an alternative to recursive estimation schemes.

Dealing with Multi-Experiment Data and Merging Models  

This demo shows how to deal with multiple experiments and merging models when working with System Identification Toolbox for estimating and refining models.

A Two Tank System - Single-Input Single-Output Nonlinear ARX and Hammerstein-Wiener Models  

In this demo we illustrate the basic commands of System Identification Toolbox for the development of single-input-single-output (SISO) nonlinear black box models from data.

A Motorized Camera - Multi-Input Multi-Output Nonlinear ARX and Hammerstein-Wiener Models  

In this demo we illustrate the basic commands of System Identification Toolbox for the estimation of multi-input-multi-output (MIMO) nonlinear black box models from data.

Nonlinear ARX Models with Custom Regressors  

In this demo we illustrate the use of custom regressors in nonlinear ARX (IDNLARX) models, with examples of single-input-single-output (SISO) and multi-input-multi-output (MIMO) systems.

Creating IDNLGREY Model Files  

In this tutorial we will concentrate on general aspects on how to implement IDNLGREY m and C MEX model files.

A Two Tank System: C MEX-File Modeling of Time-Continuous SISO System  

The purpose of this demo is firstly to show how to perform IDNLGREY modeling based on C MEX modeling files and secondly to provide a rather simple example where nonlinear state space modeling really pays off.

Narendra-Li Benchmark System: MATLAB File Modeling of a Discrete-Time System  

This demo considers identification of a complex nonlinear discrete-time system with one input and one output.

Friction Modeling: MATLAB File Modeling of Static SISO System  

In this demo we illustrate how static friction modeling can be carried out using IDNLGREY.

A Signal Transmission System: C MEX-File Modeling Using Optional Input Arguments  

This tutorial considers the use of optional input arguments to IDNLGREY. The discussion will concentrate on how to do this for C-MEX types of model files, yet to some minor extent we will also address the most relevant parallels to MATLAB file modeling.

Represent Nonlinear Dynamics Using MATLAB File for Grey-Box Estimation  

In this demo we go through the basic commands for constructing, estimating and analyzing IDNLGREY models.

An Industrial Three-Degrees-of-Freedom Robot: C MEX-File Modeling of MIMO System Using Vector/Matrix Parameters  

This tutorial describes how to design C-MEX model files that involve scalar, vector as well as matrix parameters.

A Non-Adiabatic Continuous Stirred Tank Reactor: MATLAB File Modeling with Simulations in Simulink^®  

In this tutorial we use a chemical reaction system as a modeling basis to illustrate how to include and simulate an IDNLGREY model within Simulink^®.