
Advances 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 MoreZ-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 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 MoreWhy Digital Beamforming Is Useful for Radar
Learn how you can use digital beamformers to improve the performance and functions of radar systems. The MATLAB Tech Talk series on radar covered how to use radar to determine range, range...
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 MoreSystem Identification: Koopman with Control
This lecture provides an overview of the use of modern Koopman spectral theory for nonlinear control. In particular, we develop control in a coordinate system defined by eigenfunctions of...
See MoreAdvances in feedforward control for measurable disturbances (in Spanish)
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 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 MoreKoopman Spectral Analysis (Control)
In this video, we explore extensions of Koopman theory for control systems. Much of the excitement and promise of Koopman operator theory is centered around the ability to represent...
See MoreWhy Choose Model-Based Reinforcement Learning?
What is the difference between model-free and model-based reinforcement learning? Explore the differences and results as the learning models are applied to balancing a cart/pole system as an...
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 MoreBridging the Gap: Using Real World Problems to Unveil Deep Control Principle...
This is a plenary lecture given at the 2020 IEEE Conference on Control Systems Technology, Montreal, Canada, August 24-26, 2020. There is no paper, but this is the video of the talk.
See MoreFull Stack Deep Learning
There are many great courses to learn how to train deep neural networks. However, training the model is just one part of shipping a deep learning project. This course teaches full-stack...
See MoreNo! Not Laplace Transforms
In my 13-year industrial career, I never used Laplace transforms. However, transfer functions and block diagram notation are efficient methods to describe dynamic behaviors, and are often...
See MoreSystem Identification: Regression Models
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 MoreThe Demod Squad: A Tutorial on the Utility and Methodologies for Using Modul...
Video talk of the paper by the same name.
See MoreYann LeCun’s Deep Learning Course at CDS
This course concerns the latest techniques in deep learning and representation learning, focusing on supervised and unsupervised deep learning, embedding methods, metric learning...
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 MorePID Controller Implementation in Software
How to implement a PID controller in software using C, discussing theory and practical considerations. Demonstration of PID controller code using a custom flight simulator.
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 MoreOnline Fault Detection for a DC Motor
Program embedded processors to estimate parameters and detect changes in motor dynamics in real time using System Identification Toolbox™.
See MoreProjectile Motion Practice Problems
In this video, practice along questions on an important topic of Kinematics i.e Projectile Motion. Practicing would help you remember the concepts and also understand them better.
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 MoreLearning Dynamic Systems & Control Engineering with a Video Game
Engineering Students at Northern Illinois University are learning one of their core subjects, Dynamic Systems & Control, with the aid of a video game.
See MoreDynamic Mode Decomposition (Overview)
In this video, we introduce the dynamic mode decomposition (DMD), a recent technique to extract spatio-temporal coherent structures directly from high-dimensional data. DMD has been widely...
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