
Randomized Singular Value Decomposition (SVD)
This video describes how to use recent techniques in randomized linear algebra to efficiently compute the singular value decomposition (SVD) for extremely large matrices.
See MoreIntro to Process Control
I discuss the motivation and introduce the logic behind controllers that engineers design to respond to errors in outputs (deviations from set points). P and...
See MoreStanford CS234: Reinforcement Learning | Winter 2019 | Lecture 15 - Batch Re...
Professor Emma Brunskill
Assistant Professor, Computer Science
Stanford AI for Human Impact Lab
Stanford Artificial Intelligence Lab
Statistical Machine Learning Group
Essence of Linear Algebra: Understand the Geomterical Beauty in Linear Algeb...
Linear Algebra is a very important and fundamental topic needed in almost every field of STEM. While the linear part of it is easy to understand and perform operations on, the geometric...
See MoreSVD: Eigenfaces 3 [Matlab]
This video describes how the singular value decomposition (SVD) can be used to efficiently represent human faces, in the so-called "eigenfaces" (Matlab code, part 3).
See MoreRouth Array and Stability
I show how we can find the range of allowed controller gains for a system that will allow us to maintain stability using a Routh Array.
See MoreControl Bootcamp: Example Frequency Response (Bode Plot) for Spring-Mass-Da...
This video shows how to compute and interpret the Bode plot for a simple spring-mass-damper system.
See MoreStandard 2nd Order ODEs: Natural Frequency and Damping Ratio
In this video we discuss writing 2nd order ODEs in standard form xdd(t)+2*zeta*wn*xd(t)+wn^2*x(t)where zeta = damping ratio wn = natural ...
See MoreNumerically Calculating Partial Derivatives
In this video we discuss how to calculate partial derivatives of a function using numerical techniques. In other words, these partials are calculated withou...
See MorePeter 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...
See MoreData-Driven Control: Balanced Truncation and BPOD Example
In this lecture, we explore balanced truncation and BPOD on a numerical example in Matlab.
See MoreMachine Learning Control: Tuning a PID Controller with Genetic Algorithms
This lecture shows how to use genetic algorithms to tune the parameters of a PID controller. Tuning a PID controller with genetic algorithms is not generally recommended, but is used to...
See MoreGain and Phase Margins Explained!
In this video I explain gain and phase margins. If you are confused by this topic I hope this video will help tie all of the concepts together that go into understanding what gain and phase...
See MoreThe Inverse Laplace Transform
In this video we show how to perform the inverse Laplace transform on a signal in the Laplace domain to obtain its equivalent representation in the time doma...
See MoreAuto 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...
See MoreUnderstanding Model Predictive Control, Part 7: Adaptive MPC Design with Sim...
In this video, you will learn how to design an adaptive MPC controller for an autonomous steering vehicle system whose dynamics change with respect to the longitudinal velocity. After you...
See MoreUnderstanding and Sketching Individual Bode Plot Components
In this video we illustrate how 7 types of simple transfer functions contribute to a bode plot. We refer to these as ‘components’ and will cover the followi...
See MoreTikZ source Code: Feedback passivity index
TikZ source Code: Feedback passivity index
See MoreDynamic Mode Decomposition (Code)
In this video, we code up the dynamic mode decomposition (DMD) in Matlab and use it to analyze the fluid flow past a circular cylinder at low Reynolds number.
See MoreSimple Examples of PID Control
In this video I continue the topic of PID control. We walk through a simple control system and visualize how each of the three paths, P, I, and D, all address specific problems that arise...
See MoreDerivation of the 2D Wave Equation
In this video we derive the 2D wave equation. This partial differential equation governs the motion of waves in a plane and is applicable for thin vibrating...
See MoreTikZ source Code: Lyapunov Lure
TikZ source Code: Lyapunov Lure
See MoreDenoising Data with FFT [Matlab]
This video describes how to clean data with the Fast Fourier Transform (FFT) in Matlab.
See MoreFrequency domain – tutorial 8: frequency spectra
In this video, we learn about frequency spectra which can be divided into two parts: phase and magnitude spectrum. Some examples will be provided to practice...
See MoreThe Fast Fourier Transform Algorithm
Here I discuss the Fast Fourier Transform (FFT) algorithm, one of the most important algorithms of all time.
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