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System Identification Toolbox 7.3

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


Last Week downloads: 3
Total downloads: 1,504
  • Last Updated: Apr 2, 2009
  • License: Shareware N/A
  • OS: Windows Vista/2003/XP
  • Requirements: For Matlab

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For System Identification Toolbox 7.3Publisher's description


System Identification Toolbox is a Home & Education software developed by The MathWorks, Inc.. After our trial and test, the software is proved to be official, secure and free. Here is the official description for System Identification Toolbox:

BSEditor: System Identification Toolbox lets you construct mathematical models of dynamic systems from measured input-output data. This data-driven approach helps you describe systems that are not easily modeled from first principles or specifications, such as chemical Processes and engine dynamics. It also helps you simplify detailed first-principle models, such as finite-element models of structures and Flight dynamics models, by fitting simpler models to their simulated responses.

Models obtained with System Identification Toolbox are well suited for simulation, Prediction, and control system design using products such as Simulink, Control System Toolbox, and Model Predictive Control Toolbox (all available separately).

System Identification Toolbox lets you fit linear and nonlinear models to data, a process known as black-box modeling. Available model structures include low-order process models, transfer functions, state-space models, linear models with static nonlinearities at the inputs or outputs, and nonlinear autoregressive models. If you have a mathematical model of the system dynamics, you can tune its parameters to better match experimental data, a process known as grey-box modeling.

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

Key Features
Identifies linear and nonlinear models from time- and Frequency-domain data
Simplifies identification of first-, second-, and third-order continuous-time models
Analyzes measured data and advises on data quality, required preprocessing, and presence of feedback or nonlinearities
Provides data processing tools for detrending, filtering, and reconstructing missing data
Provides Simulink blocks for simulating identified models and transferring data to and from the MATLAB workspace
Provides an interface for using linear models in Control System Toolbox (available separately)
you can free download System Identification Toolbox 7.3 now.

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