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...

Machine Learning Control: Tuning a PID Controller with Genetic Algorithms (P...

This lecture shows how to use genetic algorithms to tune the parameters of a PID controller. Tuning a PID controller with genetic algorithms is not generally recommended, but is used to...

Reinforcement Learning for Engineers, Part 3: Policies and Learning Algorith...

This video provides an introduction to the algorithms that reside within the agent. We’ll cover why we use neural networks to represent functions and why you may have to set up two neural...

Modeling Physical Systems, An Overview

This video sets the stage for the topics that I want to cover over the next month or two. This is an overview of how you go from a physical system to a linear model where you can design a...

Understanding Kalman Filters, Part 2: State Observers

Learn the working principles of state observers, and discover the math behind them. State observers are used for estimating the internal states of a system when you can’t directly measure...

Control Systems in Practice, Part 9: The Step Response

This video covers a few interesting things about the step response. We’ll look at what a step response is and some of the ways it can be used to specify design requirements for closed loop...

Adaptive Control Basics: What Is Model Reference Adaptive Control?

Use an adaptive control method called model reference adaptive control (MRAC). This controller can adapt in real time to variations and uncertainty in the system that is being controlled...

Control Systems in Practice, Part 7: 4 Ways to Implement a Transfer Function...

In some situations, it is easier to design a controller or a filter using continuous, s-domain transfer functions. We have a lot of mathematical tools that make analyzing and manipulating...

An Introduction to Multi-Agent Reinforcement Learning

Learn what multi-agent reinforcement learning is and some of the challenges it faces and overcomes. You will also learn what an agent is and how multi-agent systems can be both cooperative...

Understanding the Z-Transform

This intuitive introduction shows the mathematics behind the Z-transform and compares it to its similar cousin, the discrete-time Fourier transform. Mathematically, the Z-transform is...

Advances in Feedforward Control for Measurable Disturbances (slides)

These slides present several contributions to improve the feedforward control approaches when inversion problem arise:  the ideal compensator may not be realizable due to negative delay...

Guaranteed Margins for LQR Regulators

John Doyle's famous paper! He presents a counterexample that shows that are no guaranteed margins for LQG systems. 

MIMO Radar: TI Application Report

MIMO radar is a key technology in improving the angle resolution (spatial resolution) of mmwave-radars. This article introduces the basic principles of the MIMO-radar and the different...

Discrete 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.

Control Systems in Practice, Part 4: Why Time Delay Matters

Time delays exist in two varieties: signal distorting delays, like phase lag, in which each frequency is delayed by a different amount of time, resulting in a distorted signal shape; and non...

A Tutorial on PES Pareto Methods for Analysis of Noise Propagation in Feedba...

This paper represents a tutorial on the so called PES Pareto methodology of analyzing the sources of noise in a feedback loop. Originally conceived for analyzing noise contributors in...

Understanding Control Systems: Open-Loop Control Systems

This video explores open-loop control systems by walking through some introductory examples.

Learn how open-loop systems are found in everyday appliances like toasters or showers, and...

Radar 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...

RADAR Engineering

Radar technology is used widely today. The principles involved are very fundamental and every engineering student studies them at least once. This playlist covers Radar Engineering for an EE...

Machine Learning & Text Processing Lectures

This is the video lecture collection by Victor Lavrenko.

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...

Creating Discrete-Time Models

This MATLAB example shows how to create discrete-time linear models using the tf, zpk, ss, and frd commands.

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...

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...