
Type
Experience
Scope
Trimming and Linearization, Part 1: What is Linearization?
Why go through the trouble of linearizing a model? To paraphrase Richard Feynman, it’s because we know how to solve linear systems. With a linear model we can more easily design a controller...
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 MoreKoopman 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...
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 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 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 MoreMPCTools: Nonlinear Model Predictive Control Tools for CasADi (Python Interf...
This Python package is a collection of model predictive control tools that build on CasADi by providing a simpler interface. Along with the python package, there are a bunch of example files...
See MoreWhy Choose Deep Learning? Deep Learning for Engineers, Part 1
This video introduces deep learning from the perspective of solving practical engineering problems. The goal is to provide an introduction to the range of practical engineering problems that...
See MoreControl Systems in Practice, Part 8: The Gang of Six in Control Theory
When analyzing feedback systems, we can get caught up thinking solely about the relationship between the reference signal and the output. However, to fully understand how a feedback system...
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 MoreSystems modeling and representations (French)
Complete course on systems modeling. Includes examples, MATLAB code, and quizzes.
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 MoreMachine Learning & Text Processing Lectures
This is the video lecture collection by Victor Lavrenko.
See More3-DOF Orientation Tracking with IMUs
This document is not meant to be a comprehensive review of orientation tracking for virtual reality applications but rather an intuitive introduction to inertial measurement units (IMUs) and...
See MoreRadar Systems Engineering MATLAB Documentation and Examples
The functions in this section give you the MATLAB tools needed to evaluate the performance of a radar system. You can use the radar equation to evaluate the radar received signal-to-noise...
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 MoreUnderstanding Control Systems: The Disturbance Rejection Problem
This video provides a demonstration using a car to show how you can simulate open- and closed-loop systems in Simulink®.
First, you will learn how to model and tune open-loop systems. The...
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 MoreArtificial Intelligence
This lecture discusses artificial intelligence (AI) in the context of data science and machine learning.
See MoreDiscrete control #2: Discretize! Going from continuous to discrete domain
This is the second video in the discrete control series. It focuses on discretizing a continuous system - getting to the z-domain from the s-domain.
See MoreWhat's a Control System and Why Should I Care?
This paper is designed as a primer for college level STEM students about to take their first formal class in feedback control systems. This means that the explanations assume the reader has...
See MoreAlgorithms for Automated Driving
Each chapter of this (mini-)book guides you in programming one important software component for automated driving. Currently, this book contains two chapters: Lane Detection, and Control...
See MoreControl Bootcamp: Kalman Filter Example in Matlab
This lecture explores the Kalman Filter in Matlab on an inverted pendulum on a cart.
See MoreWhy 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...
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 More