Final Value Theorem

In this video we discuss the Final Value Theorem. Given a signal in the Laplace domain, this allows us to predict the steady state value of the signal in th...

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Unitary Transformations and the SVD [Python]

This video describes how the singular value decomposition (SVD) is related to unitary transformations, with Python code.

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TikZ source Code: matlab2tikz example

TikZ source Code: matlab2tikz example

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Drone Simulation and Control, Part 5: Tuning the PID controller

In the last video, we learned how accurate, nonlinear models are great for simulation but they don’t lend themselves well to linear analysis and design. This video takes the nonlinear model...

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Heat Transfer Demonstration

In this video we demonstrate heat transfer through a metal bar. By heating one side of the bar we can impose a non-uniform temperature distribution across t...

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Computing the DFT Matrix

This video discusses how to compute the Discrete Fourier Transform (DFT) matrix in Matlab and Python. In practice, the DFT should usually be computed using the fast Fourier transform (FFT)...

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Frequency domain – tutorial 2: Fourier series

In this video, we learn Fourier series which enables us to travel from time to the frequency domain when a signal is periodic. The following materials are co...

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Euler Angles and the Euler Rotation Sequence

 

In this video we discuss how Euler angles are used to define the relative orientation of one coordinate frame to another.

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The Fast Fourier Transform (FFT)

Here I introduce the Fast Fourier Transform (FFT), which is how we compute the Fourier Transform on a computer. The FFT is one of the most important algorithms of all time.

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Time domain - tutorial 1: what is signal processing?

In this video, we review the concept of signal processing and why it is useful to learn it. Learn Signal Processing 101 in 31 lectures covering time, frequen...

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Control Systems in Practice, Part 6: What Are Non-Minimum Phase Systems?

We like to categorize transfer functions into groups and label them because it helps us understand how a particular system will behave simply by knowing the group that it’s part of. We gain...

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Inputs and Outputs as defined by a Process Control Engineer

Defining process inputs and outputs is a lot more complicated than I initially thought when I was learning about process control. In this video, I share how ...

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Lecture 9: Time response and Time domain specifications

In this lecture, Time response is discussed in detail. Also discussed are different time domain specifications See More

Introduction to Deep Learning by Andrew NG [COMPLETE]

Andrew Ng's course on deep learning and neural networks.

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Frequency domain – tutorial 10: modulation

In this video, we learn about modulation technique which is commonly used in communication systems to send information from transmitter to receiver. The foll...

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IMC PID Design with Dead Time

IMC PID Design with Dead Time

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TUTORIAL on Stability and Routh Hurwitz criterion

Numerical problems on Stability and Routh Hurwitz criterion have been discussed in this video. See More

Stanford CS234: Reinforcement Learning | Winter 2019 | Lecture 10 - Policy G...

Professor Emma Brunskill
Assistant Professor, Computer Science
Stanford AI for Human Impact Lab
Stanford Artificial Intelligence Lab
Statistical Machine Learning Group

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Humans, Robots, and Non-Prehensile Manipulation

This is a fun video that was inspired by a presentation I saw at the 2015 International Conference on Robotics and Automation (ICRA). I wanted to see if humans could duplicate the...

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Koopman Spectral Analysis (Multiscale systems)

In this video, we discuss recent applications of data-driven Koopman theory to multi-scale systems.

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Peter Ponders PID - Controlling an Under Damp Mass and Spring System

Demonstrates:How to calculate the PID gains. The importance of the derivative gain. How to simulate the mass and spring systemControl limitations based on s...

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Understanding PID Controller

This blog post begins by walking through the basics and the theoretical part of the PID controllers.  The controller is then tested, verified, and analyzed using MATLAB.

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Control Bootcamp: Sensitivity and Complementary Sensitivity

Here we explore the sensitivity and complementary sensitivity functions, which are critical in understanding robustness and performance.

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Understanding Sensor Fusion and Tracking, Part 2: Fusing a Mag, Accel, and G...

This video describes how we can use a magnetometer, accelerometer, and a gyro to estimate an object’s orientation. The goal is to show how these sensors contribute to the solution, and to...

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Controllability, Reachability, and Eigenvalue Placement [Control Bootcamp]

This lecture explains the equivalence of controllability, reachability, and the ability to arbitrarily place eigenvalues of the closed loop system.

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