Create linear and nonlinear dynamic system models from measured input-output data

System Identification Toolbox™ provides MATLAB® functions, Simulink® blocks, and an app for constructing mathematical models of dynamic systems from measured input-output data. It lets you create and use models of dynamic systems not easily modeled from first principles or specifications. You can use time-domain and frequency-domain input-output data to identify continuous-time and discrete-time transfer functions, process models, and state-space models. The toolbox also provides algorithms for embedded online parameter estimation.

The toolbox provides identification techniques such as maximum likelihood, prediction-error minimization (PEM), and subspace system identification. To represent nonlinear system dynamics, you can estimate Hammerstein-Wiener models and nonlinear ARX models with wavelet network, tree-partition, and sigmoid network nonlinearities. The toolbox performs grey-box system identification for estimating parameters of a user-defined model. You can use the identified model for system response prediction and plant modeling in Simulink. The toolbox also supports time-series data modeling and time-series forecasting.


Capabilities

Model Identification from Data

Create models from measured input-output data.

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Linear Model Identification

Estimate multi-input multi-output continuous or discrete-time transfer functions with a specified number of poles and zeros.

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Nonlinear Model Identification

Estimate nonlinear models, such as nonlinear ARX and Hammerstein-Wiener.

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Parameter Estimation in User-Defined Models

Specify the model structure and estimate its parameters using nonlinear optimization techniques.

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Online Parameter Estimation

Use Simulink blocks for online parameter estimation.

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Time-Series Data Modeling

Create time-series data models to forecast future signal values based on previous ones.

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Product Resources

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Documentation

Explore documentation for System Identification Toolbox functions and features, including release notes and examples.

Functions

Browse the list of available System Identification Toolbox functions.

Blocks

View a Simulink library of blocks that System Identification Toolbox supports.

System Requirements

View system requirements for the latest release of System Identification Toolbox.

Technical Articles

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User Stories

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Community and Support

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Apps

System Identification Toolbox apps enable you to quickly access common tasks through an interactive interface.


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Have Questions?

Aditya

Contact Aditya Baru,
System Identification Toolbox Technical Expert

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System Identification Toolbox requires MATLAB.


Related Solutions

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News and Events

Learn about system identification from professor Lennart Ljung
Program embedded processors to estimate parameters and detect changes in motor dynamics in real time using System Identification Toolbox™.
MathWorks engineers will introduce new capabilities for online parameter estimation and will explain and demonstrate how these capabilities can be used for fault detection and adaptive control. The webinar will begin with an overview of recently deve

Introduction to System Identification