
Introduction to Anomaly Detection for Engineers
Anomaly detection is the process of identifying events or patterns that differ from expected behavior. This is important for applications like predictive maintenance but can be hard to...
See MoreAn Artificial Intelligence Primer
This blog post is a great primer providing definitions for basic terms used in AI and machine learning (ML) such as supervised learning, unsupervised learning, and transfer learning...
See MorePole Placement for the Inverted Pendulum on a Cart [Control Bootcamp]
Here we use the 'place' command in Matlab to design full-state feedback gains to specify the eigenvalues of the closed-loop system. This is demonstrated on the inverted pendulum on a cart.
See MoreedX course: Dynamics and Control
This is an interactive course about the basic concepts of Systems, Control and their impact in all the human activities. First, the basic concepts of systems, dynamics, structure and control...
See MoreGain a better understanding of Root Locus Plots using Matlab
In this video I go through various ways to use Matlab to plot and visualize the root locus.
See MoreMathworks Model Reference Adaptive Control Overview
This website provides an overview of the mathematics behind Model Reference Adaptive Control (MRAC). MRAC is a model-based, real-time adaptive control algorithm that computes control actions...
See MoreIntro to Data Science: Overview
This lecture provides an introductory overview to data science. I will discuss the high-level goals of this lecture series, and how data science is about asking and answering questions with...
See MoreAutonomous Navigation, Part 6: Metrics for System Assessment
Take a systems engineering approach to verifying the autonomous navigation system end to end and learn how simulations and physical tests can complement each other. The video also covers a...
See MoreControl Systems in Practice, Part 1: What Control Systems Engineers Do
This video walks through the phases of a typical project and describes what it means to be a control systems engineer. It covers the concept formulation phase, in which your job is to help...
See MoreNonlinear System Identification | System Identification, Part 3
Learn about nonlinear system identification by walking through one of the many possible model options: A nonlinear ARX model. Brian Douglas covers the importance of adding an offset term to...
See MoreControlling Robotic Swarms
Come with me to the Robotics, Aerospace, and Information Networks lab at the University of Washington to learn the basics of swarm robotics. Find out how simple distributed algorithms can...
See MoreMachine Learning Control: Overview
This lecture provides an overview of how to use machine learning optimization directly to design control laws, without the need for a model of the dynamics.
See MoreVideo Lectures on Automatic Control
A collection of 32 video lectures on automatic control by Dr. Rajesh Joseph Abraham.
See MoreRobotic Car - A Simple Way to Build a Model
You don't always have to work out the math in order to build up a model of your system. Sometimes generating a model is as easy as running a simple test and inspecting the results. I show...
See MoreLectures on Modelling and Control of Dynamic Systems (French)
Lectures on Modelling and Control of Dynamic Systems from Patrick Lanusse of Bordeaux INP, France.
See MoreMy Sole Advise to Data Scientists on Coursera & Quora
This blog post by Tarry Singh answers questions including "How do I get started in the field on Machine Learning, Deep Learning or Artificial Intelligence" and "How do I advance from the...
See MoreDirectivity and Antenna Gain - radartutorial.eu
This page describes antenna directivity and gain. The directivity of an antenna is the ratio of the power density S (radiant intensity per unit area) of the real antenna in its main...
See MoreMachine Learning: What is easy, medium, and hard?
This video gives a brief overview of what is easy, medium, and hard in machine learning, explored through case studies. Progress in machine learning is rapidly advancing, and changing the...
See MoreSystems Engineering, Part 4: An Introduction to Requirements
Get an introduction to an important tool in systems engineering: requirements. You'll learn about the three things every requirement must have and what makes a requirement valid. You'll also...
See MoreWhat are Transfer Functions? | Control Systems in Practice
This video introduces transfer functions - a compact way of representing the relationship between the input into a system and its output. It covers why transfer functions are so popular and...
See MorePID Explained
A qualitative explanation of P, I, & D actions using graphs.
See MoreIntroduction to Classic Control Theory (Japanese)
A collection of video lectures by Yuki Nishimura covering an introduction to classic control theory.
See MoreControl Bootcamp: Limitations on Robustness
This video describes some of the fundamental limitations of robustness, including time delays and right-half plane zeros.
See MoreIntro to Data Science: Historical Context
This lecture provides some historical context for data science and data-intensive scientific inquiry.
See MoreUsing Transfer Learning | Deep Learning for Engineers, Part 4
This video introduces the idea of transfer learning. Transfer learning is modifying an existing deep network architecture and then retraining it to accomplish your task rather than the task...
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