Understanding Kalman Filters, Part 4: An Optimal State Estimator Algorithm

Discover the set of equations you need to implement a Kalman filter algorithm. You’ll learn how to perform the prediction and update steps of the Kalman filter algorithm, and you’ll see how...

The Radar Equation | Understanding Radar Principles

Learn how the radar equation combines several of the main parameters of a radar system in a way that gives you a general understanding of how the system will perform. The radar equation is a...

Reinforcement Learning for Engineers, Part 2: Understanding the Environment ...

In this video, we build on our basic understanding of reinforcement learning by exploring the workflow. We cover what an environment is and some of the benefits of training within a...

DC Motor Speed: System Modeling

This examples walks through modeling a simple DC motor in MATLAB.

Using the Control System Designer in Matlab

In this video we show how to use the Control System Designer to quickly and effectively design control systems for a linear system. We show how to add multi...

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...

Understanding PID Control, Part 6: Manual and Automatic Tuning Methods

The previous video showed three different approaches to developing a mathematical model of your physical system. Now that we have this model, we can use it to tune a PID controller that will...

Autonomous Navigation, Part 4: Path Planning with A* and RRT

This video explores some of the ways that we can use a map like a binary occupancy grid for motion and path planning. We briefly cover what motion planning means and how we can use a graph...

Understanding Kalman Filters, Part 3: An Optimal State Estimator

Watch this video for an explanation of how Kalman filters work. Kalman filters combine two sources of information, the predicted states and noisy measurements, to produce optimal, unbiased...

FMCW Radar for Autonomous Vehicles | Understanding Radar Principles

Watch an introduction to Frequency Modulated Continuous Wave (FMCW) radar and why it’s a good solution for autonomous vehicle applications. This demonstration will show how FMCW radar can...

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...

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...

How Kalman Filters Work, Part 1

This article looks at four popular estimation filter architectures: particle filter, sigma point filter, extended Kalman filter, and the Kalman filter. It discusses how all four of these...

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...

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...

Learning From Data

This is an introductory course in machine learning (ML) that covers the basic theory, algorithms, and applications. ML is a key technology in Big Data, and in many financial, medical...

Intro to Data Science: The Nature of Data

This lecture discusses the types of data you might encounter, and how it determines which techniques to use.

Model Reference Adaptive Control of Aircraft Undergoing Wing Rock

This example shows how to control roll and roll rate of a delta wing aircraft undergoing wing rock. For this example, the system model is unknown. Therefore, you use model reference adaptive...

But what is the Fourier Transform? A visual introduction.

An animated introduction to the Fourier Transform.

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...

MATLAB Example: Solve Constrained Nonlinear Optimization, Problem-Based

This example shows how to find the minimum of a nonlinear objective function with a nonlinear constraint by using the problem-based approach. 

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...

Algorithms to Antenna: Increasing Angular Resolution Using MIMO Radar

Articles in Microwaves & RF that talks about how forming virtual arrays with multiple-input, multiple-output waveforms makes it possible to generate more focused beam patterns.

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...

Nyquist Stability Criterion, Part 1

An explanation of the Nyquist Stability Criterion. This video steps through the importance of the criterion, how to interpret the Nyquist plot graphically, and why it is the way it is....