The Taylor Series

In this video we discuss the Taylor Series (and the closely related Maclaurin Series). These are two specific types of Power Series that allow you to approx...

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Machine Learning - Andrew Ng, Stanford University

Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech...

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Trimming a Model of a Dynamic System Using Numerical Optimization

In this video we show how to find a trim point of a dynamic system using numerical optimization techniques. We generate a cost function that corresponds to a straight and level flight...

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Peter Ponders PID - IAE,ITAE,ISE Performance indicators

Performance indicators can be used to compute closed loop pole locations. Only one gain parameter is required to move the pole locations closer to the origi...

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Control Systems Lectures - Closed Loop Control

This lecture discusses the differences between open loop and closed loop control.

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Sketching Root Locus Part 1

Sketching a root locus by hand can be done by following some simple rules. However, more important than actually being able to sketch to plot is being able to use our knowledge to design...

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How the Flight Controller Code Works - dRehmFlight VTOL

This video will walk you through the flight controller code of dRehmFlight VTOL to give you a better understanding of the contents and structure. The hope is that it will cover almost...

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Auto Tuning a Small DC Motor in Torque Mode

I was really testing the picture in picture feature of the Screen Flow software I use to make these videos. I knew the auto tuning would work. I kept the v...

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Parseval's Theorem

Parseval's theorem is an important result in Fourier analysis that can be used to put guarantees on the accuracy of signal approximation in the Fourier domain.

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Control Bootcamp: Full-State Estimation

This video describes full-state estimation. An estimator dynamical system is constructed, and it is shown that the estimate converges to the true state. Further, the eigenvalues of the...

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Lecture 13: Stability and Routh Hurwitz criterion

In this video, stability of LTI systems has been discussed. BIBO stability has also been explained. Further, Routh Hurwitz criterion is also explained See More

Singular Value Decomposition (SVD): Dominant Correlations

This lectures discusses how the SVD captures dominant correlations in a matrix of data.

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Solving the 2D Wave Equation

In this video, we solve the 2D wave equation. We utilize two successive separation of variables to solve this partial differential equation. Topics discuss...

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Lecture 27: Lead Compensator Design using Bode plots

In this video lecture, design of a lead compensator using Bode plots is discussed. A numerical example has also been taken up See More

SVD: Image Compression [Python]

This video describes how to use the singular value decomposition (SVD) for image compression in Python.

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Laplace domain – tutorial 5: Inverse Laplace transform

In this video, we cover inverse Laplace transform which enables us to travel back from Laplace to the time domain. We will learn how to use simple tricks alo...

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Lecture 32: Linearisation and State Space Fundamentals

This video introduces State Space techniques. Also covered is, Linearisation See More

Linear Regression 1 [Python]

This video describes how the singular value decomposition (SVD) can be used for linear regression in Python (part 1).

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Frequency domain – tutorial 3: filtering (periodic signals)

In this video, we learn about filtering which enables us to manipulate the frequency content of a signal. A common filtering application is to preserve desi...

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Bode Plots by Hand: Real Constants

This video describes the benefit of being able to approximate a Bode plot by hand and explains what a Bode plot looks like for a simple transfer function; a real constant.

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Matrix Completion and the Netflix Prize

This video describes how the singular value decomposition (SVD) can be used for matrix completion and recommender systems.

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IMC Design of an Unstable Process Example

In this video, I cover how we can use IMC method to rigorously design a controller for an inherently unstable process (has a positive pole).

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Stanford CS234: Reinforcement Learning | Winter 2019 | Lecture 11 - Fast Rei...

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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dRehmFlight VTOL - Teensy (Arduino) Flight Controller and Stabilization

dRehmFlight VTOL is a new flight controller and stabilization package intended to be used for small to medium sized hobby or research projects. dRehmFlight is the code, and the physical...

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Data-Driven Control: Balanced Proper Orthogonal Decomposition

In this lecture, we introduce the balancing proper orthogonal decomposition (BPOD) to approximate balanced truncation for high-dimensional systems.

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