Kalman Filter Virtual Lab

The Kalman Filter virtual laboratory contains interactive exercises that let you study linear and extended Kalman filter design for state estimation of a simple pendulum system. The virtual...

System Identification Methods

System Identification is the process of determining the model or the equations of motion for your system. This is incredibly important because basing a control system design off of a bad...

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...

Introduction to Noise Filtering

Introduction to filtering - moving average, first-order, anti-aliasing, set point softening

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...

Linear Algebra Review

This short course is a quick review of linear algebra, intended for students who have already taken a previous course in linear algebra or have some experience with vectors and matrices. The...

TinyEKF: Lightweight C/C++ Extended Kalman Filter with Python for prototypin...

TinyEKF is a simple C/C++ implementation of the Extended Kalman Filter that is general enough to use on different projects. In order to make it practical for running on Arduino, STM32, and...

Z-Transform - Practical Applications

Covering practical applications of the Z-transform used in digital signal processing, for example, stability analysis and frequency response of discrete-time systems. Theory, C code, and...

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...

What Are Dynamic Models? Chapter 1 from Dynamic Models in Biology

Throughout this book we use a wide-ranging set of case studies to illustrate different aspects of models and modeling. In this introductory chapter we describe and give examples of different...

Understanding PID Control, Part 4: A PID Tuning Guide

It can be difficult to navigate all the resources that promise to explain the secrets of PID tuning. Some proclaim that PID tuning is an art that requires finesse and experience, while...

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...

Kalman Filter Design

This example shows how to perform Kalman filtering. Both a steady state filter and a time varying filter are designed and simulated.

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...

What's a Control System and Why Should I Care? A whirlwind tour through the ...

This paper aims to provide some introduction, a cheat sheet, and some context for college level STEM students about to take that first controls class. In some cases, it provides context...

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...

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...

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...

Discrete Fourier Transform

The discrete Fourier transform, or DFT, is the primary tool of digital signal processing. The foundation of the product is the fast Fourier transform (FFT), a method for computing the DFT...

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...

DC Motor Speed: System Modeling

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

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 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...

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...