Скачать с ютуб System identification with Julia: 8 Subspace-based identification в хорошем качестве

System identification with Julia: 8 Subspace-based identification

We illustrate how to use subspace-based identification, such as N4SID, MOESP, CVA etc. to fit dynamical models to noisy data. Subpsace-based methods can be viewed as Dynamic Mode Decomposition (DMD) for real data, with noise and disturbances. System identification with Julia is an introductory video series about system identification, the art and science of estimating dynamical models using input-output data and the Julia programming language. Notebook file: https://juliahub.com/ui/Notebooks/fre... 00:00 Subspace id intro 03:35 The noisy data 04:46 Spectra of data 05:58 Frequency-domain estimate 06:56 Subspace estimation 08:54 Residual analysis 09:30 Singular value spectrum 11:11 Simulation 11:34 Bode plots 13:00 Try without noise 16:56 Comparison to PEM Throughout the series, we will use the tools JuliaSim and ControlSystemIdentification, detailed below. Find out more about subspaceid: https://baggepinnen.github.io/Control... JuliaSim is an online platform providing enterprise solutions for modeling, simulation and control in Julia, building on ControlSystems.jl, see https://juliahub.com/products/juliasim/ with control-specific documentation available https://help.juliahub.com/juliasimcon... For classical system identification in Julia, see https://baggepinnen.github.io/Control... Please leave a comment if there is a particular system-identification related topic you would like to learn about! Got questions or feedback? We'd love to hear from you! Fill out the contact form below, and our team will get back to you as soon as possible. https://share.hsforms.com/1ax_TNnP2S5...