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Developing Models from Experimental Data using System Identification Toolbox 1.0

  Date Added: August 27, 2013  |  Visits: 273

Developing Models from Experimental Data using System Identification Toolbox

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These files support the webinar titled "Developing Models from Experimental Data Using System Identification Toolbox". The webinar was presented on April 05, 2007 and can be found at:http://www.mathworks.com/wbnr30317For other webinars and demos related to System Identification Toolbox, please visit: http://www.mathworks.com/products/sysid/Contents:1. webinar_walk_through.m: contains all the linear and nonlinear estimation examples presented during the webinar.2. Data files and Simulink models: process_data.mat, ExampleModel.mdl, Friction_Model.mdl. Any other data files used in the presentation already ship with the toolbox (ver 7.0).Products used:- You basically need only System Identification Toolbox (SITB) to try out most examples.- To use Simulink blocks, you would, of course, need Simulink.- Control System Toolbox is used at one place to show how estimated models can be converted into LTI objects (SS, TF etc)- Optimization Toolbox will be used if available for grey box estimation. If not, SITB's built-in optimizers will be used automatically.- Other products mentioned: Neural Network Toolbox, Model Predictive Control Toolbox and Robust Control Toolbox. http://www.mathworks.com/matlabcentral/fx_...ntification.zip

Requirements: No special requirements
Platforms: Matlab
Keyword: Basically Blocks Control Converted Estimated Examplemodelmdl Friction Modelmdl Model Network Neural Objects Optimization Place Presentation Process Datamat Products Toolbox
Users rating: 0/10

License: Freeware Size: 30.72 KB
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