Stanford CS234: Reinforcement Learning | Winter 2019 | Lecture 10 - Policy G...

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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Understanding Model Predictive Control, Part 3: MPC Design Parameters

To successfully control a system using an MPC controller, you need to carefully select its design parameters. This video provides recommendations for choosing the controller sample time...

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Dynamic Modeling in Process Control

I'll show you how we can build the dynamic models necessary to derive process transfer functions as an introduction to process control.

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Understanding PID Controller

This blog post begins by walking through the basics and the theoretical part of the PID controllers.  The controller is then tested, verified, and analyzed using MATLAB.

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PID Control - A brief introduction

In this video, I introduce the topic of PID control. This is a short introduction design to prepare you for the next few lectures where I will go through several examples of PID control....

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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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Equations of Motion for a Planar Vehicle

In this video we outline equations of motion for a simple planar vehicle. This model is suitable for vehicles such as boats or hovercraft that that are rest...

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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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Using a Homogeneous Transformation Matrix to Combine Rotation and Translatio...

In this video we discuss how to properly deal with coordinate frames that are both rotated and translated from one another. We develop a homogeneous transfo...

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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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Routh-Hurwitz Criterion, Beyond Stability

This video explains of few uses of the Routh-Hurwitz Criterion that go beyond simply determining how many poles exist in the right half plane. I cover how to determine gain margin and how...

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The 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...

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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

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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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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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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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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Cayley-Hamilton Theorem [Control Bootcamp]

Here we describe the Cayley-Hamilton Theorem, which states that every square matrix satisfies its own characteristic equation. This is very useful to prove results related to...

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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

Frequency domain – tutorial 2: Fourier series

In this video, we learn Fourier series which enables us to travel from time to the frequency domain when a signal is periodic. The following materials are co...

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Control Bootcamp: Linear Quadratic Gaussian (LQG)

This lecture combines the optimal full-state feedback (e.g., LQR) with the optimal full-state estimator (e.g., LQE or Kalman Filter) to obtain the sensor-based linear quadratic Gaussian (LQG...

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Robust Principal Component Analysis (RPCA)

Robust statistics is essential for handling data with corruption or missing entries. This robust variant of principal component analysis (PCA) is now a workhorse algorithm in several fields...

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Tutorial on Root Locus

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

Time domain - tutorial 1: what is signal processing?

In this video, we review the concept of signal processing and why it is useful to learn it. Learn Signal Processing 101 in 31 lectures covering time, frequen...

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Machine Learning Control: Genetic Algorithms

This lecture provides an overview of genetic algorithms, which can be used to tune the parameters of a control law.

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