The Navigation Equations: Computing Position North, East, and Down

In this video we show how to compute the inertial velocity of a rigid body in the vehicle-carried North, East, Down (NED) frame. This is achieved by rotating the velocity expressed in the...

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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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Data-Driven Control: The Goal of Balanced Model Reduction

In this lecture, we discuss the overarching goal of balanced model reduction: Identifying key states that are most jointly controllable and observable, to capture the most input—output...

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Bode Plots of Complex Transfer Functions

In this video we discuss how to generate a bode plot of a complex transfer function by decomposing it into the individual components. We then show how one c...

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Derivation of Rodrigues’ Rotation Formula

In this video we explain and derive Rodrigues’ Rotation Formula. This functions describes how to rotate an arbitrary vector about another arbitrary axis of rotation. This has applications to...

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Identifying Dominant Balance Physics from Data - Jared Callaham

This video illustrates a new algorithm to identify local dominant physical balance relations from multiscale spatiotemporal data.

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Dynamic Mode Decomposition (Examples)

In this video, we continue to explore the dynamic mode decomposition (DMD). In particular, we look at recent methodological extensions and application areas in fluid dynamics, disease...

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SVD Method of Snapshots

This video describes how to compute the singular value decomposition (SVD) using the method of snapshots, by Sirovich 1987.

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Peter Ponders PID - Feed Forward Theory and Calculations

The formulas for feed forwards are derived for motors and hydraulic actuators. See More

Denoising Data with FFT [Python]

This video describes how to clean data with the Fast Fourier Transform (FFT) in Python.

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Relationship Between Poles and Performance of a Dynamic System

In this video we establish the relationship between pole locations and associated performance of a dynamic system. This relationship is useful to translate ...

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Unitary Transformations

This video discusses unitary matrix transformations and how they relate to the geometry of the singular value decomposition (SVD).

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The Fourier Transform and Convolution Integrals

This video describes how the Fourier Transform maps the convolution integral of two functions to the product of their respective Fourier Transforms.

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Laplace domain – tutorial 2: Region of Convergence (ROC)

In this video, we learn five golden rules on how to quickly find the Region of Convergence (ROC) of Laplace transform. Learn Signal Processing 101 in 31 lect...

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Control Bootcamp: Loop Shaping Example for Cruise Control

This video demonstrates loop shaping on the cruise control model.

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Finding Transfer Functions from Response Graphs

Given a system response to a unit step change, in this video I'll cover how we can derive the transfer function so we can predict how our system will respond...

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Control Systems with MATLAB - Root Locus

Few root locus examples have been explained in this video using MATLAB comand rltool. Also, the MATLAB GUI called rltool with which user can click and insert... See More

Time domain - tutorial 2: signal representation

In this video, we review how to represent information as a signal. The information can be anything such as voice (1D) or an image (2D) or even a video (3D). ...

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Second Order Dynamics Example

How will a second order process respond in the time domain when subjected to a unit step input? What other behaviors can we expect to see and why? Tune in to...

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Control Systems with MATLAB - Modelling

This video explains how to find the inverse Laplace transform of a time function using MATLAB. Also, this demonstrates how to find the transfer function of e... See More

Stanford CS234: Reinforcement Learning | Winter 2019 | Lecture 12 - 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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Control Bootcamp: Observability

This video explores the observability of a linear system, namely the ability to estimate the full state "x(t)" from a time-history of limited output measurements "y(t)".

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Introduction to System Stability and Control

This video attempts to provide an intuitive understanding of concepts like stability and stability margin. I briefly describe both of these topics with examples and explain how you can...

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The Laplace Transform - A Graphical Approach

A lot of books cover how to perform a Laplace Transform to solve differential equations. This video tries to show graphically what the Laplace Transform is doing and why figuring out the...

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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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