Singular Value Decomposition (SVD): Dominant Correlations

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

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Time domain - tutorial 11: system properties from impulse response

In this video, we learn how to find system properties from the impulse response. Specifically, memoryless, causal, stable and invertible systems will be ful...

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Data-Driven Control: Balancing Transformation

In this lecture, we derive the balancing coordinate transformation that makes the controllability and observability Gramians equal and diagonal. This is the critical step in balanced model...

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Control 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...

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Dynamic Behavior and Input Types in Process Control

An introduction to the four types of dynamic behavior and five types of inputs (step, ramp, pulse, impulse, and sinusoidal), and why transfer functions are u...

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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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Peter Ponders PID - Integrated Time Absolute Error - 4 Pole example

This video shows how to calculate the coefficients for a 4 pole ITAE and how to use the 4 pole ITAE to calculate closed loop controller gains.

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Machine 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".

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Intro 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...

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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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Peter Ponders PID - FeedForwards - Basics - What they do

The video shows the importance of using feed forwards to reduce error while following a motion profile. See More

Neural Networks and Deep Learning

This lecture explores the recent explosion of interest in neural networks and deep learning in the context of 1) vast and increasing data sets, and 2) rapidly improving computational...

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Routh 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.

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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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Nonhomogeneous Linear Ordinary Differential Equations

In the previous video (https://youtu.be/3Kox-3APznI) we examined solving homogeneous linear ordinary differential equations (the forcing function was equal t...

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Control Systems with MATLAB - Time Domain Analysis

Time domain analysis has been carried out using MATLAB in this video. Second order systems have been discussed in detail. How to obtain different time domain... See More

Partial Fraction Expansion/Decomposition

In this video we discuss how to perform partial fraction expansion (PFE) to rewrite a ratio of polynomials as simpler expressions. Topics and time stamps:(0...

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Tutorial on Root Locus

Few numerical problems using Root locus has been explained in this video See More

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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Time Domain Analysis: Performance Metrics for a First Order System

In this video we introduce the concept of time domain analysis for dynamic systems. We examine a first order dynamic system and derive how various performan...

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Koopman Spectral Analysis (Representations)

In this video, we explore how to obtain finite-dimensional representations of the Koopman operator from data, using regression.

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Solving the 1D Heat Equation

In this video we simplify the general heat equation to look at only a single spatial variable, thereby obtaining the 1D heat equation. We solving the result...

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Why Learn Control Theory

In this video I present a few reasons why learning control theory is important and try to give some motivation to continue learning.

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Standing Waves Demonstration

In this video we demonstrate standing waves. We show how the system can be excited by oscillating at specific frequencies to generating standing waves. The...

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Degrees of Controllability and Gramians [Control Bootcamp]

This lecture discusses degrees of controllability using the controllability Gramian and the singular value decomposition of the controllability matrix.

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