ITCLI: An Interactive Tool for Closed-Loop Identification

The Interactive Tool for Closed-Loop Identification (ITCLI) is an interactive software tool for understanding SISO closed-loop identification using prediction-error techniques. The tool...

Advances in feedforward control for measurable disturbances

The efficient compensation of load disturbances is one of the most important tasks in any control system. Most industrial processes are affected by disturbances and only feedback is commonly...

Z-Transform - Practical Applications

Covering practical applications of the Z-transform used in digital signal processing, for example, stability analysis and frequency response of discrete-time systems. Theory, C code, and...

Interactive Tool for PID understanding

The module PID Basics is designed to explore the properties of a simple feedback loop by showing the time and frequency responses of a closed-loop system and demonstrating how these...

The Institute for Systems Theory and Automatic Control MATLAB Apps

The Institute for Systems Theory and Automatic Control offers 5 Matlab Apps on the topics of the Nyquist Criterion, Robustness and Stability, Loopshaping, Controllability and Observability...

Koopman Spectral Analysis (Control)

In this video, we explore extensions of Koopman theory for control systems. Much of the excitement and promise of Koopman operator theory is centered around the ability to represent...

i-pIDtune: An interactive tool for integrated system identification and PID ...

i-pIDtune is an interactive software tool that integrates system identification and PID controller design. The tool supports experimental design and execution under plant-friendly conditions...

ITCRI: An Interactive Software Tool for Control-Relevant Identification

The Interactive Tool for Control Relevant Identification (ITCRI) comprehensively captures the control-relevant identification process, from input design to closed-loop control, depicting...

Matlab Radar Designer App

The Radar Designer app is an interactive tool that assists engineers and system analysts with high-level design and assessment of radar systems at the early stage of radar development. Using...

Vibrational Control in Insect Flight

Abstract: It is generally accepted among biology and engineering communities that insects are unstable at hover. However, existing approaches that rely on direct averaging do not fully...

Why Digital Beamforming Is Useful for Radar

Learn how you can use digital beamformers to improve the performance and functions of radar systems. The MATLAB Tech Talk series on radar covered how to use radar to determine range, range...

Data-Driven Dynamical Systems Overview

This video provides a high-level overview of this new series on data-driven dynamical systems. In particular, we explore the various challenges in modern dynamical systems, along with...

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...

Interactive Tools for Control Purposes

This resource provides different links to Interactive Tools that can be used for control education. Interactive Tools are very powerful educational resources as support to learning and...

Why Choose Model-Based Reinforcement Learning?

What is the difference between model-free and model-based reinforcement learning? Explore the differences and results as the learning models are applied to balancing a cart/pole system as an...

Various games for learning Controller Design

Since 2005, we are using educational games in the course „Einführung in die Regelungstechnik“ (Introduction to automatic control). 

The project started with the game spaceballRT, which uses...

Advances in feedforward control for measurable disturbances (in Spanish)

The efficient compensation of load disturbances is one of the most important tasks in any control system. Most industrial processes are affected by disturbances and only feedback is commonly...

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...

How I put the Google Maps Algorithm on my Autonomous Drone

This fully autonomous drone has an onboard computer ‘brain’, camera ‘eyes’, and an algorithm that generates the fastest path around unknown obstacles as they’re detected mid-flight. Let’s...

Bridging the Gap: Using Real World Problems to Unveil Deep Control Principle...

This is a plenary lecture given at the 2020 IEEE Conference on Control Systems Technology, Montreal, Canada, August 24-26, 2020. There is no paper, but this is the video of the talk.

Dynamic Mode Decomposition (Overview)

In this video, we introduce the dynamic mode decomposition (DMD), a recent technique to extract spatio-temporal coherent structures directly from high-dimensional data. DMD has been widely...

Android and iPhone E-Learning App for Nyquist Stability Criterion

In our Nyquist App, you can analyze the stability of the closed loop by using the Nyquist stability criterion. With the Nyquist stability criterion, you can determine the stability of the...

Principal Component Analysis (PCA) 2 [Python]

This video describes how the singular value decomposition (SVD) can be used for principal component analysis (PCA) in Python (part 2).

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...

Kristin Pettersen Lectures on Nonlinear Control

Kristin Pettersen Lectures on Nonlinear Control, including many of the necessary mathematical tools and concepts.