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...

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...

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...

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...

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...

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...

Introduction: PID Controller Design

In this tutorial we will introduce a simple, yet versatile, feedback compensator structure: the Proportional-Integral-Derivative (PID) controller. The PID controller is widely employed...

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...

The AVA Flight Computer

This video describes the board design, hardware architecture, and software components of the All Vehicle Avionics (AVA) flight computer that was designed by Joe Barnard of BPS Space.  This...

Model Predictive Control

This lecture provides an overview of model predictive control (MPC), which is one of the most powerful and general control frameworks. MPC is used extensively in industrial control settings...

Improving 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...

Process Dynamics and Control Course

This course focuses on a complete start to finish process of physics-based modeling, data driven methods, and controller design. Although some knowledge of computer programming is required...

Artificial Intelligence

This lecture discusses artificial intelligence (AI) in the context of data science and machine learning.

But what is the Fourier Transform? A visual introduction.

An animated introduction to the Fourier Transform.

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...

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...

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...

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....

Extremum 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.

A real control system - how to start designing

Let’s design a control system the way you might approach it in a real situation rather than an academic one. In this video, I step through a control problem and show how control theory is...

Control Bootcamp: Kalman Filter Example in Matlab

This lecture explores the Kalman Filter in Matlab on an inverted pendulum on a cart.

Machine Learning & Text Processing Lectures

This is the video lecture collection by Victor Lavrenko.

ITSIE: An Interactive Software Tool for System Identification Education

ITSIE is an Interactive Tool for System Identification Education. The tool is developed using Sysquake, a Matlab-like language with fast execution and excellent facilities for interactive...

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...

Linear Regression

Linear regression is a cornerstone of data-driven modeling; here we show how the SVD can be used for linear regression.