Lecture 29: State space representation

This video explains how a system can be modelled in state space form. Also shown is how to obtain transfer function from State space form See More

Lecture 19: Lead and PD compensator Design using Root Locus

This video discusses how a Proportional Derivative [PD] controller and a Lead compensator can be designed using Root Locus See More

Koopman Spectral Analysis (Overview)

In this video, we introduce Koopman operator theory for dynamical systems. The Koopman operator was introduced in 1931, but has experienced renewed interest recently because of the...

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Derivation and Solution of Laplace’s Equation

In this video we show how the heat equation can be simplified to obtain Laplace’s equation. We investigate how to solve Laplace’s equation using separation ...

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Randomized SVD: Power Iterations and Oversampling

This video discusses the randomized SVD and how to make it more accurate with power iterations (multiple passes through the data matrix) and oversampling.

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Frequency domain – tutorial 1: concept of frequency (with Chinese subtitle)

In this video, the following materials are covered:1) intuitive explanation on the frequency concept 2) what is the relation between time and frequency domai...

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Control Bootcamp: Three Equivalent Representations of Linear Systems

This video explores three equivalent representations of linear systems: State-space ODEs, Frequency domain transfer functions, and Time-domain impulse response convolution.

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Bode 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 ...

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Frequency domain – tutorial 5: Fourier transform

In this video, we learn about Fourier transform which enables us to travel from time to frequency domain when a signal is not periodic. The learning objectiv...

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Machine Learning Goals

This lecture discusses the high-level goals of machine learning, and what we want out of our models. Goals include speed and accuracy, along with interpretability, generalizability...

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Feedforward Control Intro

If we know how a disturbance will affect an output, we can proactively change our manipulated variable to counteract it.

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Stanford CS234: Reinforcement Learning | Winter 2019 | Lecture 4 - Model Fre...

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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Data-Driven Control: Balanced Truncation

In this lecture, we describe the balanced truncation procedure for model reduction, where a handful of the most controllable and observable state directions are kept for the reduced-order...

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Direct Synthesis for PID Design Intro

Direct Synthesis for PID Design Intro

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RL Course by David Silver - Lecture 10: Classic Games

An overview of Game Theory, minimax search, self-play and imperfect information games.

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Introduction 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...

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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

Control Bootcamp: Benefits of Feedback on Cruise Control Example (Part 2)

Here we investigate the benefits of feedback for systems with uncertain dynamics and disturbances, as illustrated on a cruise control example. (Part 2)

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Cartesian, Polar, Cylindrical, and Spherical Coordinates

In this video we discuss Cartesian, Polar, Cylindrical, and Spherical coordinates as well as develop forward and reverse transformations to go from one coord...

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The Fourier Transform

This video will discuss the Fourier Transform, which is one of the most important coordinate transformations in all of science and engineering.

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Understanding Sensor Fusion and Tracking, Part 1: What Is Sensor Fusion?

This video provides an overview of what sensor fusion is and how it helps in the design of autonomous systems. It also covers a few scenarios that illustrate the various ways that sensor...

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Gain 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...

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Transfer Functions: Introduction and Implementation

In this video we introduce transfer functions and show how they can be derived from a set of linear, ordinary differential equations. We also examine how to...

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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

Control Systems Lectures - Transfer Functions

This lecture describes transfer functions and how they are used to simplify modeling of dynamic systems.

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