Control Systems Lectures - Closed Loop Control

This lecture discusses the differences between open loop and closed loop control.

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Stanford CS234: Reinforcement Learning | Winter 2019 | Lecture 6 - CNNs and ...

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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Principal Component Analysis (PCA)

Principal component analysis (PCA) is a workhorse algorithm in statistics, where dominant correlation patterns are extracted from high-dimensional data.

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Visually Determining Transfer Functions

Process Control classes can get pretty hard to follow when you lose sight of what transfer functions really are. How do you get them in the first place?

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Introduction to the Fourier Transform (Part 2)

This video is the second part of the introduction to the Fourier Transform. I address an error that I made in the first video concerning the scaling term of the transform. I also try to...

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RL Course by David Silver - Lecture 8: Integrating Learning and Planning

Introduces model-based RL, along with integrated architectures and simulation based search.

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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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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.

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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

Linearizing a Simulink Model Using the Linear Analysis Tool and ‘linmod’

In this video we show how to linearize a non-linear Simulink model using numerical techniques. This approach is extremely powerful as it allows automatic ge...

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SVD: 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).

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Standard HW Problem #2: Which is the real open loop transfer function?

In this video, we’ll go through another standard homework problem so you can see how you can apply many of the things you’re learning into a single problem. The question is, we have two...

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Control 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.

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Time Domain Analysis with Matlab: Using the Linear System Analyzer

In this video we explore various Matlab functions and workflows to perform time domain analysis of a dynamic system. This includes the use of ‘tf’, ‘step’, ...

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TikZ source Code: Dashed box

TikZ source Code: Dashed box

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Digital Twin Parameter Tuning

Learn how to tune the digital twin model of a pump system to its physical asset using Simulink Design Optimization™. You can use measured data collected from the physical system to tune the...

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Derivation of the Heat Equation

In this video, we derive the heat equation. This partial differential equation (PDE) applies to scenarios such as the transfer of heat in a uniform, homogen...

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Machine Learning and Cross-Validation

This lecture discusses the importance of cross-validation to assess models obtained via machine learning.

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TikZ source Code: Switching Manifold

TikZ source Code: Switching Manifold

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Euler Angles and the Euler Rotation Sequence

 

In this video we discuss how Euler angles are used to define the relative orientation of one coordinate frame to another.

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Data-Driven Control: Error Bounds for Balanced Truncation

In this lecture, we derive error bounds for the balanced truncation.

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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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Understanding Model Predictive Control, Part 2: What is MPC?

Learn how model predictive control (MPC) works. Using a simple car example, this video provides insight into an MPC controller’s strategy for finding the optimal steering wheel angle to...

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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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Laplace Transforms to Derive Transfer Functions

Once we have a state space model, we will take a Laplace Transform to derive the transfer function to determine the response of an output relative to an inpu...

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