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Lennart Ljung on System Identification Toolbox: History and Development

2,435 views · Published 4 December 2014 · 4:12 · Indexed 12 November 2026

Channel: MATLAB · 2014 · Science & Technology

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Professor Lennart Ljung describes how he developed System Identification Toolbox™ and why he chose to write it in MATLAB®.

For more videos about System Identification Toolbox, visit: http://www.mathworks.com/products/sysid/videos.html 

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.

The principal architect of the toolbox is Professor Lennart Ljung, a recognized leader in the field of system identification.

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