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...

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...

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...

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...

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...

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...

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...

MATLAB Example: Online Recursive Least Squares Estimation

This example shows how to implement an online recursive least squares estimator. You estimate a nonlinear model of an internal combustion engine and use recursive least squares to detect...

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...

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...

MATLAB scripts for "Nonlinear System Identification | System Identification,...

This Github repo contains the data files and MATLAB scripts that were used in "Nonlinear System Identification | System Identification, Part 3".

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.

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...

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...

MATLAB Scripts for video "Linear System Identification | System Identificati...

This Github repo contains the data files and MATLAB scripts that were used in the MATLAB Tech Talk video "Linear System Identification | System Identification, Part 2" 

What are Polynomial Models?

This Mathworks page provides an overview of polynomial models. 

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...

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...

Two Tank System: C MEX-File Modeling of Time-Continuous SISO System

This MATLAB example shows how to perform IDNLGREY modeling based on C MEX model files. It uses a simple system where nonlinear state space modeling really pays off.

System Identification: DMD Control Example

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

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...

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...

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...

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...

Data based modeling of nonlinear dynamic systems using System Identification...

Using an engine throttle valve modeling example, this demo shares some perspectives on creation of nonlinear models of dynamic systems from the measurements of its input and outputs. It...