Discrete control #4: Discretize with the matched method

This is the fourth video on discrete control and in this video we are going to continue exploring the different techniques we can use to discretize a continuous system and talk about the...

Extremum Seeking Control in Matlab

This lecture explores extremum-seeking control (ESC) on a simple example in Matlab. In particular, a discrete-time (digital) version of ESC is coded in a Matlab script.

Conventional and Adaptive Beamformers

This example illustrates how to apply digital beamforming to a narrowband signal received by an antenna array. Three beamforming algorithms are illustrated: the phase shift beamformer...

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...

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...

Simulating Test Signals for a Radar Receiver

This example shows how to simulate received signal of a monostatic pulse radar to estimate the target range. A monostatic radar has the transmitter collocated with the receiver. The...

But what is the Fourier Transform? A visual introduction.

An animated introduction to the Fourier Transform.

Virtual Labs for control education

This resource provides different links to virtual and remote labs that can be used for control education. Virtual and remote labs are very powerful tools for learning and teaching, that...

Increasing Angular Resolution with Virtual Arrays

This MATLAB example introduces how forming a virtual array in MIMO radars can help increase angular resolution. It shows how to simulate a coherent MIMO radar signal processing chain using...

EGGN 510 - Lecture 02-1 Digital Image Fundamentals

This is a video lecture of EGGN 510 Image and Multidimensional Signal Processing by William Hoff.

MATLAB Function: ztrans

ztrans(f) finds the Z-Transform of f. By default, the independent variable is n and the transformation variable is z. If f does not contain n, ztrans uses symvar. 

Using the Reinforcement Learning Toolbox™ to Balance an Inverted Pendulum

Reinforcement learning (RL) is a subset of Machine Learning that uses dynamic data, not static data like unsupervised learning or supervised learning. Reinforcement learning is used in many...

MATLAB Example: Fault Detection Using an Extended Kalman Filter

This example shows how to use an extended Kalman filter for fault detection. The example uses an extended Kalman filter for online estimation of the friction of a simple DC motor...

Model predictive control python toolbox

do-mpc is a comprehensive open-source toolbox for robust model predictive control (MPC) and moving horizon estimation (MHE). do-mpc enables the efficient formulation and solution of control...

Block Diagram Algebra

In this video we introduce block diagrams (AKA signal flow diagrams). We explore how they are used to describe complex systems as well as how to perform blo...

Discrete control #3: Designing for the zero-order hold

This is the third video on discrete control and in this video, I want to clear up a confusion that I caused last time regarding using the ZOH method to discretize a continuous controller and...

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...

Using Simscape™ to Model a Quanser QUBE-Servo 2 with Friction

Modelling a DC servomotor is one of the common examples used in control system textbooks and courses. Given that so many systems use DC motors, e.g. robot manipulator arms, it’s an important...

Understanding Closed-Loop Control

This lecture discusses the differences between open loop and closed loop control in a very easy and intuitive way. Daily examples, like a dishwasher, plant irrigation, and car speed systems...

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...

Improving the Beginner's PID - Introduction

In conjunction with the release of the new Arduino PID Library Brett has released this series of posts that explain his PID code. He start's with what he call's “The Beginner’s PID.”  He...

Discrete control #6: z-plane warping and the bilinear transform

We’re continuing our journey through discrete control and in this video, we’re going to expand our understanding of the bilinear transform. Along the way, we’ll learn about how this...

Nyquist Stability Criterion, Part 2

An explanation of the Nyquist Stability Criterion part 2. This video steps through the how to sketch a Nyquist plot by hand, what to do if there are open loop pools on the imaginary axis...

Kalman Filter Simulink 2022A example

This model is intended to help illustrate how a Kalman filter can estimate the state of a system. The "real system" is a nonlinear model of the Temperature Control Lab by Prof. John...

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...