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...

Z-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...

Vibrational 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...

System 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...

Data-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...

Why 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...

MATLAB 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...

Algorithms 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...

Koopman 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...

Why 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...

Advances 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...

Model Reference Adaptive Control of Aircraft Undergoing Wing Rock

This example shows how to control roll and roll rate of a delta wing aircraft undergoing wing rock. For this example, the system model is unknown. Therefore, you use model reference adaptive...

MATLAB Example: Fault Detection Using an Extended Kalman Filter

This example shows how to use an extended Kalman filter for fault detection. The example uses an extended Kalman filter for online estimation of the friction of a simple DC motor...

How I put the Google Maps Algorithm on my Autonomous Drone

This fully autonomous drone has an onboard computer ‘brain’, camera ‘eyes’, and an algorithm that generates the fastest path around unknown obstacles as they’re detected mid-flight. Let’s...

Learning 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.

Simulink example: Adaptive MPC Control of Nonlinear Chemical Reactor Using O...

This example shows how to use an Adaptive MPC controller to control a nonlinear continuous stirred tank reactor (CSTR) as it transitions from low conversion rate to high conversion rate.

A...

Geodetic Coordinates: Computing Latitude and Longitude

In this video we show how to compute the geodetic latitude and terrestrial longitude if given the velocity north and east. This is useful for simulating a body moving over a spheroid Earth...

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...

System 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...

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...

Dynamic 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...

Principal Component Analysis (PCA) 2 [Python]

This video describes how the singular value decomposition (SVD) can be used for principal component analysis (PCA) in Python (part 2).

Bridging 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.

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...

Kristin Pettersen Lectures on Nonlinear Control

Kristin Pettersen Lectures on Nonlinear Control, including many of the necessary mathematical tools and concepts.