
Type
Experience
Scope
What Is Extremum Seeking Control? | Learning-Based Control
Get an introduction to extremum seeking control—an adaptive control method for finding an optimal control input or set of system parameters without needing a model of your system, static...
See MoreUnderstanding Control Systems: Feedback Control Systems
This video provides introductory examples to learn about the basics of feedback control (closed-loop control) systems.
Learn how feedback control is used to automate processes and discover...
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 MoreFixed-Point HDL-Optimized Minimum-Variance Distortionless-Response (MVDR) Be...
This example shows how to implement a fixed-point HDL-optimized minimum-variance distortionless-response (MVDR) beamformer in MATLAB.
See MorePerspectives on Control-Relevant Identification Through the Use of Interacti...
This paper presents a control-relevant identification methodology through an intuitive interactive tool called "Interactive Tool for Control Relevant Identification (ITCRI)". ITCRI...
See MoreAlgorithms for Automated Driving
Each chapter of this (mini-)book guides you in programming one important software component for automated driving. Currently, this book contains two chapters: Lane Detection, and Control...
See More3-DOF Orientation Tracking with IMUs
This document is not meant to be a comprehensive review of orientation tracking for virtual reality applications but rather an intuitive introduction to inertial measurement units (IMUs) and...
See MoreUnderstanding Kalman Filters, Part 5: Nonlinear State Estimators
This video explains the basic concepts behind nonlinear state estimators, including extended Kalman filters, unscented Kalman filters, and particle filters.
A Kalman filter is only defined...
See MoreMATLAB Example: Online Recursive Least Squares Estimation
This example shows how to implement an online recursive least squares estimator. You estimate a nonlinear model of an internal combustion engine and use recursive least squares to detect...
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 MoreNyquist Stability Criterion, Part 2
An explanation of the Nyquist Stability Criterion part 2. This video steps through the how to sketch a Nyquist plot by hand, what to do if there are open loop pools on the imaginary axis...
See MoreAlgorithms to Antenna: Increasing Angular Resolution Using MIMO Radar
Articles in Microwaves & RF that talks about how forming virtual arrays with multiple-input, multiple-output waveforms makes it possible to generate more focused beam patterns.
See MoreInteractive Tools for Control Purposes
This resource provides different links to Interactive Tools that can be used for control education. Interactive Tools are very powerful educational resources as support to learning and...
See MoreCreating Discrete-Time Models
This MATLAB example shows how to create discrete-time linear models using the tf
, zpk
, ss
, and frd
commands.
Intro to Data Science: The Nature of Data
This lecture discusses the types of data you might encounter, and how it determines which techniques to use.
See MoreDrone Simulation and Control, Part 1: Setting Up the Control Problem
Quadcopters and other styles of drones are extremely popular, partly because they have sophisticated programmed control systems that allow them to be stable and fly autonomously with very...
See MoreRADAR Engineering
Radar technology is used widely today. The principles involved are very fundamental and every engineering student studies them at least once. This playlist covers Radar Engineering for an EE...
See MoreAdvances in Feedforward Control for Measurable Disturbances (slides)
These slides present several contributions to improve the feedforward control approaches when inversion problem arise: the ideal compensator may not be realizable due to negative delay...
See MoreWhat Is Fuzzy Logic | Fuzzy Logic Part 1
This video introduces fuzzy logic and explains how you can use it to design a fuzzy inference system (FIS), which is a powerful way to use human experience to design complex systems...
See MoreVibrational Control in Insect Flight
Abstract: It is generally accepted among biology and engineering communities that insects are unstable at hover. However, existing approaches that rely on direct averaging do not fully...
See MoreUnderstanding Control Systems: Open-Loop Control Systems
This video explores open-loop control systems by walking through some introductory examples.
Learn how open-loop systems are found in everyday appliances like toasters or showers, and...
See MoreMatlab Radar Designer App
The Radar Designer app is an interactive tool that assists engineers and system analysts with high-level design and assessment of radar systems at the early stage of radar development. Using...
See MoreGuaranteed Margins for LQR Regulators
John Doyle's famous paper! He presents a counterexample that shows that are no guaranteed margins for LQG systems.
See MoreData-Driven Dynamical Systems Overview
This video provides a high-level overview of this new series on data-driven dynamical systems. In particular, we explore the various challenges in modern dynamical systems, along with...
See MoreITCRI: An Interactive Software Tool for Control-Relevant Identification
The Interactive Tool for Control Relevant Identification (ITCRI) comprehensively captures the control-relevant identification process, from input design to closed-loop control, depicting...
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