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.
Discover more about System Identification Toolbox by exploring these resources.
Explore documentation for System Identification Toolbox functions and features, including release notes and examples.
Browse the list of available System Identification Toolbox functions.
View a Simulink library of blocks that System Identification Toolbox supports.
View system requirements for the latest release of System Identification Toolbox.
View articles that demonstrate technical advantages of using System Identification Toolbox.
Read how System Identification Toolbox is accelerating research and development in your industry.
Find answers to questions and explore troubleshooting resources.
System Identification Toolbox apps enable you to quickly access common tasks through an interactive interface.
System Identification Toolbox requires MATLAB.
Use System Identification Toolbox to solve scientific and engineering challenges: