MATLAB Function: phased.MVDRBeamformer

The phased.MVDRBeamformer System object™ implements a narrowband minimum-variance distortionless-response (MVDR) beamformer. The MVDR beamformer is also called the Capon beamformer. An MVDR...

Control Systems in Practice, Part 8: The Gang of Six in Control Theory

When analyzing feedback systems, we can get caught up thinking solely about the relationship between the reference signal and the output. However, to fully understand how a feedback system...

EGGN 510 - Lecture 02-1 Digital Image Fundamentals

This is a video lecture of EGGN 510 Image and Multidimensional Signal Processing by William Hoff.

Manuscript about ITISE: an Interactive Software Tool for System Identificati...

The paper describes the conceptual basis, main features and functionality of an interactive software tool developed in support of system identification education and discovery.

This...

Discrete control #6: z-plane warping and the bilinear transform

We’re continuing our journey through discrete control and in this video, we’re going to expand our understanding of the bilinear transform. Along the way, we’ll learn about how this...

Using the Reinforcement Learning Toolbox™ to Balance an Inverted Pendulum

Reinforcement learning (RL) is a subset of Machine Learning that uses dynamic data, not static data like unsupervised learning or supervised learning. Reinforcement learning is used in many...

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...

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...

MIMO Radar: TI Application Report

MIMO radar is a key technology in improving the angle resolution (spatial resolution) of mmwave-radars. This article introduces the basic principles of the MIMO-radar and the different...

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...

MATLAB Documentation page: nlarx command

This is the Mathworks documentation page for the nlarx MATLAB command.

Pole Placement for the Inverted Pendulum on a Cart [Control Bootcamp]

Here we use the 'place' command in Matlab to design full-state feedback gains to specify the eigenvalues of the closed-loop system. This is demonstrated on the inverted pendulum on a cart.

Full 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...

Projectile Motion Equations and Theory

In this video, an important topic under 2D Kinematics i.e. Projectile Motion, is covered. Its theory, equations, and examples are thoroughly discussed.

Computing Euler Angles: Tracking Attitude Using Quaternions

In this video we continue our discussion on how to track the attitude of a body in space using quaternions. The quaternion method is similar to the Euler Ki...

Virtual Lab for a Two-tanks system

This is a virtual lab for a two-tank system that can be used for modelling and control learing/teaching purposes. Open-loop tests and closed-loop simulatons based on PI control or PI plus...

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...

Averaging 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...

Introduction to Classic Control Theory (Japanese)

A collection of video lectures by Yuki Nishimura covering an introduction to classic control theory.

Android and iPhone E-Learning App for Nyquist Stability Criterion

In our Nyquist App, you can analyze the stability of the closed loop by using the Nyquist stability criterion. With the Nyquist stability criterion, you can determine the stability of the...

Understanding Valve Flow Characteristics

The response of flow rate through a control valve depends on the friction losses in the piping in which it is installed as well as the controller signal.  The installed characteristic (a...

Extremum Seeking Control

This lecture provides an overview of extremum-seeking control (ESC), which is an adaptive equation free method of controlling nonlinear systems. A sinusoidal perturbation is added to the...

Autonomous Navigation, Part 6: Metrics for System Assessment

Take a systems engineering approach to verifying the autonomous navigation system end to end and learn how simulations and physical tests can complement each other. The video also covers a...

Control Loop Foundation Batch and Continuous Processes - Interactive Source ...

Control Loop Foundation contains workshops that allow the reader to get hands on experience through this web interface. Once a lab is selected, then you may access workshop directions and...

A Hybrid Lab Experience: Blending Hands-on Explorations with the Flexibility...

This case study examines how the Earth and Space Science and Engineering (ESSE) department at York University in Toronto offered a meaningful remote laboratory experience to over 180...