
How Antennas Work
Antennas constitute as a major component in various communication systems, signal transmission and many others. It is important to understand how they work and create propagating waves in...
See MoreProcess 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...
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 MoreModel 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)
See MoreSystem Identification: Full-State Models with Control
This lecture provides an overview of modern data-driven regression methods for linear and nonlinear system identification, based on the dynamic mode decomposition (DMD), Koopman theory, and...
See MoreA Tutorial on PES Pareto Methods for Analysis of Noise Propagation in Feedba...
This is the recorded talk of the paper by the same title.
See MoreWind 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...
See MoreControl Bootcamp: Cautionary Tale About Inverting the Plant Dynamics
Here we show an example of why it can be a very bad idea to invert some plant dynamics, for example with unstable eigenvalues, for loop shaping.
See MoreUnderstanding Sensor Fusion and Tracking, Part 6: What Is Track-Level Fusion...
Gain insights into track-level fusion, the types of tracking situations that require it, and some of the challenges associated with it.
You’ll see two different tracking architectures—track...
See MoreNathan Kutz:"Data-driven Discovery of Governing Physical Laws"
Seminar by Dr.Nathan Kutz on "Data-driven Discovery of Governing Physical Laws" on 10/31/2018 CICS Seminar Series
See MoreCS224n: Natural Language Processing with Deep Learning | Winter 2021
This course covers the foundations of the effective modern methods for deep learning applied to NLP, a big picture understanding of human languages and the difficulties in understanding and...
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 MoreRadar Design with the 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.
See MoreInteractive Course for Control Theory
Control Theory is a topic that finds a widespread application throughout engineering and natural sciences. It is very common in electrical, mechanical and process engineering. Especially...
See MoreData-Driven Control: Overview
Overview lecture for series on data-driven control. In this lecture, we discuss how machine learning optimization can be used to discover models and effective controllers directly from data...
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 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 MoreMulti-Agent Reinforcement Learning: Independent vs Cooperative Agents
From the Abstract:
Intelligent human agents exist in a cooperative social environment that facilitates learning. They learn not only by trialand -error, but also through cooperation by...
See MoreMath Background for Machine Learning from Carnegie Melon University
This course provides a place for students to practice the necessary mathematical background for further study in machine learning — particularly for taking 10-601 and 10-701. Topics covered...
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 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...
See MoreFeedback Systems: An Introduction for Scientists and Engineers
This is the wiki for the text Feedback Systems (second edition) by Karl J. Åström and Richard M. Murray. On this resource you will find the complete text of the book as well as additional...
See MoreAveraging Methods in Nonlinear Dynamical Systems
Perturbation theory and in particular normal form theory has shown strong growth during the last decades. So it is not surprising that the authors have presented an extensive revision of the...
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 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...
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