
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...
See MoreExtremum 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.
See MoreConventional 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...
See MoreManuscript 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...
See MoreVarious 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...
See MoreSimulating 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...
See MoreBut what is the Fourier Transform? A visual introduction.
An animated introduction to the Fourier Transform.
See MoreVirtual 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...
See MoreIncreasing 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...
See MoreEGGN 510 - Lecture 02-1 Digital Image Fundamentals
This is a video lecture of EGGN 510 Image and Multidimensional Signal Processing by William Hoff.
See MoreMATLAB 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.
See MoreUsing 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...
See MoreMATLAB 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...
See MoreModel 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...
See MoreBlock 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...
See MoreDiscrete 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...
See MoreAdvances 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...
See MoreUsing 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...
See MoreUnderstanding 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...
See MoreSystem 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...
See MoreImproving 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...
See MoreDiscrete 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...
See MoreNyquist 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...
See MoreKalman 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...
See MoreInteractive 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...
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