
Randomized SVD Code [Matlab]
This video describes the randomized singular value decomposition (rSVD) (Matlab code).
See MoreLecture 17: Introduction to Compensators/Controllers
Frequency 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 MorePosicast Control 6 - ( In English)
This video presents the transition from half-cycle to other cycles ( third-cycle, fourth-cycle,..)
See MoreControl Systems Lectures - LTI Systems
This lecture describes what it means when we say a system is linear and time invariant. I also try to give an example as to why these systems are so important when designing control systems...
See MoreBode Stability Criterion in Frequency Response Analysis Intro
The Bode stability criterion allows us to quickly determine the stability and relative stability of a transfer function. It uses a graphical method that can ...
See MoreFrequency domain – tutorial 11: equalization
In this video, we learn about equalization technique which is used in communication systems to compensate for the destructive effect of the channel between t...
See MoreMachine Learning Overview
This lecture provides an overview of machine learning, and how it fits into this introductory video sequence on data science. We discuss how machine learning involves "modeling with data".
See MoreFeedforward Control Intro
If we know how a disturbance will affect an output, we can proactively change our manipulated variable to counteract it.
See MoreStanford CS229: Machine Learning | Autumn 2018
Autumn 2018 Stanford course on machine learning by Andrew Ng.
See MoreBode Plots by Hand: Poles and Zeros at the Origin
This is a continuation of the Control Systems Lectures. 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...
See MoreNeural Networks: Caveats
This lecture discusses some key limitations of neural networks and suggests avenues of ongoing development.
See MoreDirect Synthesis for PID Design Intro
Direct Synthesis for PID Design Intro
See MorePeter Ponders PID - Closed Loop Zeros
This video covers closed loop zeros, what causes zeros and the benefits and drawbacks of closed loop zeros.
See MoreUnderstanding PID Control, Part 3: Expanding Beyond a Simple Derivative
This video describes how to make an ideal PID controller more robust when controlling real systems that don’t behave like ideal linear models. Noise is generated by sensors and is present in...
See MoreIntroduction to Ordinary Differential Equations
In this video we introduce the concept of ordinary differential equations (ODEs). We give examples of how these appear in science and engineering as well as...
See MorePeter Ponders PID- Motor position control
Drone Simulation and Control, Part 3: How to Build the Flight Code
This video describes how to create quadcopter flight software from the control architecture developed in the last video. It covers how to process the raw sensor readings and use them with...
See MoreGaussian/Normal Distributions
In this video we discuss the Gaussian (AKA Normal) probability distribution function. We show how it relates to the error function (erf) and discuss how to ...
See MoreTikZ source Code: Both passivity indices applied
TikZ source Code: Both passivity indices applied.
See MoreFourier Analysis: Overview
This video presents an overview of the Fourier Transform, which is one of the most important transformations in all of mathematical physics and engineering. This series will introduce the...
See MoreControl Bootcamp: Sensitivity and Robustness
Here we show that peaks in the sensitivity function result in a lack of robustness.
See MoreThe Routh-Hurwitz Stability Criterion
In this video we explore the Routh Hurwitz Stability Criterion and investigate how it can be applied to control systems engineering. The Routh Hurwitz Stabi...
See MoreTikZ source Code: Example Graph
TikZ source Code: Example Graph
See MoreThe Fourier Transform and Derivatives
This video describes how the Fourier Transform can be used to accurately and efficiently compute derivatives, with implications for the numerical solution of differential equations.
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