What Is System Identification? | System Identification, Part 1

Get an introduction to system identification that covers what it is and where it fits in the bigger picture. See how the combination of data-driven methods and physical intuition can improve...

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System Identification: Theory for the User

From the Back Cover

The field's leading text, now completely updated. 

Modeling dynamical systems ― theory, methodology, and applications. 

Lennart Ljung's System Identification: Theory...

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Linear System Identification | System Identification, Part 2

Learn how to use system identification to fit and validate a linear model to data that has been corrupted by noise and external disturbances Noise and disturbances can make it difficult to...

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System Identification Overview

System identification is a methodology for building mathematical models of dynamic systems using measurements of the input and output signals of the system.  This overview from Mathworks...

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Introduction to System Identification

In this webinar, you will have a unique chance to learn about system identification from a world-renowned subject expert, Professor Lennart Ljung. Professor Ljung will explain the basic...

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System Identification: Koopman with Control

This lecture provides an overview of the use of modern Koopman spectral theory for nonlinear control. In particular, we develop control in a coordinate system defined by eigenfunctions of...

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Perspectives on Control-Relevant Identification Through the Use of Interacti...

This paper presents a control-relevant identification methodology through an intuitive interactive tool called "Interactive Tool for Control Relevant Identification (ITCRI)". ITCRI...

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Manuscript about ITISE: an Interactive Software Tool for System Identificati...

The paper describes the conceptual basis, main features and functionality of an interactive software tool developed in support of system identification education and discovery.

This...

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System Identification Methods

System Identification is the process of determining the model or the equations of motion for your system. This is incredibly important because basing a control system design off of a bad...

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System Identification: Regression Models

This lecture provides an overview of modern data-driven regression methods for linear and nonlinear system identification, based on the dynamic mode decomposition (DMD), Koopman theory, and...

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Model Identification and Adaptive Control - From Windsurfing to Telecommunic...

This book is based on a workshop entitled: "Model Identification and Adap­tive Control: From Windsurfing to Telecommunications" held in Sydney, Aus­tralia, on December 16, 2000. The workshop...

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Data-Driven Control: Linear System Identification

Overview lecture on linear system identification and model reduction. This lecture discusses how we obtain reduced-order models from data that optimally capture input--output dynamics.

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What are Polynomial Models?

This Mathworks page provides an overview of polynomial models. 

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System Identification: Full-State Models with Control

This lecture provides an overview of modern data-driven regression methods for linear and nonlinear system identification, based on the dynamic mode decomposition (DMD), Koopman theory, and...

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Online and Recursive System Identification | System Identification, Part 4

Online system identification algorithms estimate the parameters and states of a model as new data is measured and available in real-time or near real-time. Brian Douglas covers what online...

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What are Nonlinear ARX Models?

This Mathworks page provides an overview of Nonlinear ARX Models.Nonlinear ARX models extend the linear ARX models to the nonlinear case. The structure of these models enables you to model...

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System Identification: Dynamic Mode Decomposition with Control

This lecture provides an overview of dynamic mode decomposition with control (DMDc) for full-state system identification. DMDc is a least-squares regression technique based on the singular...

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Nonlinear System Identification | System Identification, Part 3

Learn about nonlinear system identification by walking through one of the many possible model options: A nonlinear ARX model. Brian Douglas covers the importance of adding an offset term to...

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System Identification: DMD Control Example

This lecture gives a Matlab example of dynamic mode decomposition with control (DMDc) for full-state system identification.

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What Is Online Estimation?

This Mathworks document describes online estimation. Online estimation algorithms estimate the parameters and states of a model when new data is available during the operation of the...

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System Identification: Sparse Nonlinear Models with Control

This lecture explores an extension of the sparse identification of nonlinear dynamics (SINDy) algorithm to include inputs and control. The resulting SINDY with control (SINDYc) can be used...

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Peter Ponders PID - System Identification Basics

Transfer functions don't come with the machine you are trying to control. Transfer functions must be estimated using system identification techniques. With... See More

Peter Ponders PID - System Identification Advanced

System Identification of a more complex system with noise and truncation errors. This is the same open loop transfer function used in the root locus videohtt... See More

Identifying Dominant Balance Physics from Data - Jared Callaham

This video illustrates a new algorithm to identify local dominant physical balance relations from multiscale spatiotemporal data.

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Frequency Response Analysis FRA and the Amplitude Ratio and Phase Angle

Process engineers model output response to inputs that oscillate via frequency response analysis (FRA). In this video, I'll go over amplitude ratios and phas...

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