Controlling 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...

Autonomous Navigation, Part 3: Understanding SLAM Using Pose Graph Optimizat...

This video provides some intuition around Pose Graph Optimization—a popular framework for solving the simultaneous localization and mapping (SLAM) problem in autonomous navigation.

We’ll...

PID Explained

A qualitative explanation of P, I, & D actions using graphs.

Fast chirp FMCW Radar in automotive applications

FMCW (frequency-modulated continuous wave radar) modulations have been popularly implemented in the automotive radar applications. This document demonstrates system requirement for a new...

3D Kinematics, Free Falling, Reference Frames

Walter Lewin is one of the most reputed professors and was a former lecturer at MIT. His free to watch series on YouTube titled 8.01 is an excellent one for undergrads and high school...

Intro to Data Science: Answering Questions with Data

This lecture describes the central aspect of data science: asking and answering questions with data. In particular, we discuss the thought process and progression of questions one might ask...

Advanced process control (APC): Theory & Applications in SAGD

This webinar is presented by Thiago Avila and covers what APC is, why we do it, examples of APC in the SAGD industry, what optimization opportunities are available, and where this technology...

Directivity 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...

Data-Driven Control: Linear System Identification

Overview lecture on linear system identification and model reduction. This lecture discusses how we obtain reduced-order models from data that optimally capture input--output dynamics.

System Identification: Dynamic Mode Decomposition with Control

This lecture provides an overview of dynamic mode decomposition with control (DMDc) for full-state system identification. DMDc is a least-squares regression technique based on the singular...

Systems Engineering, Part 5: Some Benefits of Model-Based Systems Engineerin...

Learn how model-based systems engineering (MBSE) can help you cut through the chaos of early systems development and get you from definition to execution more seamlessly.

You’ll hear the...

MATLAB Discovery Page - Anomaly Detection

Anomaly detection is the process of identifying events or patterns that differ from expected behavior. Anomaly detection can range from simple outlier detection to complex machine learning...

Machine 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.

The Linear Quadratic Regulator (LQR)

Lecture notes for ECE717 on LQR control by Laurent Lessard. There is a section that shows how the Algebraic Riccati Equation is part of the LQR solution by "completing the square".

Control Bootcamp: Introduction to Robust Control

This video motivates robust control with the famous 1978 paper by John Doyle, titled "Guaranteed Margins for LQG Regulators"... Abstract: There are none.

Vibrational control of nonlinear systems: Vibrational controllability and tr...

In the first part of this work, the criteria for the existence of stabilizing parametric oscillations have been derived. In the present paper, the problem of choosing the stabilizing...

Model Reference Adaptive Control Fundamentals (Dr. Tansel Yucelen)

Forum on Robotics & Control Engineering (FoRCE, http://force.eng.usf.edu/) Seminar Series: "Model Reference Adaptive Control Fundamentals" (Dr. Tansel Yucelen)

Wind Tunnel Testing: Introduction and Data Acquisition

This is the first of our 3 part series on wind tunnel testing. In this video, we introduce the concept of wind tunnel testing as well as discuss the process for acquiring aerodynamic data in...

What are Phased Arrays?

This video introduces the concept of phased arrays. An array refers to multiple sensors, arranged in some configuration, that act together to produce a desired sensor pattern. With a phased...

Machine 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...

Sparse Identification of Nonlinear Dynamics for Model Predictive Control

This lecture shows how to use sparse identification of nonlinear dynamics with control (SINDYc) with model predictive control to control nonlinear systems purely from data.

State Space in Process Control

An overview on how we can derive a state space model from a given set of state variables and inputs, as well as an intro to deviation variables. This is part...

RL Course by David Silver - Lecture 1: Introduction to Reinforcement Learnin...

Introduces reinforcment learning (RL), an overview of agents and some classic RL problems.

Data Preprocessing and the Short-Time Fourier Transform | Deep Learning for ...

Data in its raw form might not be ideal for training a network. There are some changes we can make to the data that are often desired or sometimes necessary in order to make training faster...

Controllability and the Discrete-Time Impulse Response [Control Bootcamp]

This lecture derives the impulse response for a discrete-time system and relates this to the controllability matrix.