
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...
See MoreControl 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...
See MoreIntroducing Feedback Control to Middle and High School STEM Students, Part 2...
This paper was presented at the 2019 IFAC Advances on Control Education Conference (IFAC-ACE), Philadelphia, PA, USA, July 7-9, 2019, and is in the conference proceedings. This paper aims at...
See MoreLinear 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...
See MoreFMCW 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...
See MoreWhat 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...
See MoreUnderstanding 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...
See MoreAn 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...
See MoreInteractive Tool for PID understanding
The module PID Basics is designed to explore the properties of a simple feedback loop by showing the time and frequency responses of a closed-loop system and demonstrating how these...
See MoreAdvances in feedforward control for measurable disturbances
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 MoreIntroducing Feedback Control to Middle and High School STEM Students, Part 1...
This paper was presented at the 2019 IFAC Advances on Control Education Conference (IFAC-ACE), Philadelphia, PA, USA, July 7-9, 2019, and is in the conference proceedings. This paper aims at...
See MoreModeling 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...
See MoreSystem 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...
See MoreITCLI: An Interactive Tool for Closed-Loop Identification
The Interactive Tool for Closed-Loop Identification (ITCLI) is an interactive software tool for understanding SISO closed-loop identification using prediction-error techniques. The tool...
See MoreUnderstanding 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...
See MoreUsing 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...
See MoreKalman 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...
See MoreDC Motor Speed: System Modeling
This examples walks through modeling a simple DC motor in MATLAB.
See MoreControl 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...
See MoreAdaptive 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...
See MoreReinforcement 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...
See MoreResonance in Nature and Bioinspired Squid Robots
Bioinspired robots combine the best of both biology and engineering. Using tools learned from nature, we can build squid-like and other squishy robots to improve current capabilities in...
See MoreTrimming and Linearization, Part 2: The Practical Side of Linearization
With a general understanding of linearization, you might run into a few snags when trying to linearize realistic nonlinear models. These snags can be avoided if you have a more practical...
See Morei-pIDtune: An interactive tool for integrated system identification and PID ...
i-pIDtune is an interactive software tool that integrates system identification and PID controller design. The tool supports experimental design and execution under plant-friendly conditions...
See MoreNyquist 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....
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