Uploaded October 2022 | Updated September 2026, 2 weeks ago
This video shows how to derive the equations of motion for a fully nonlinear system, the particle in a potential well, from F=ma or from Lagrangian mechanics. We will linearize these equations and draw phase portraits to gain intuition about nonlinear systems.
Playlist: youtube.com/playlist?list=PLMrJAkhIeNNTYaOnVI3QpH7jgULnAmvPA
Course Website: http://faculty.washington.edu/sbrunton/me564/
@eigensteve on Twitter
eigensteve.com
databookuw.com
This video was produced at the University of Washington
%%% CHAPTERS %%%
0:00 Problem setup and equations of motion
5:37 Alternative derivation from Euler-Lagrange equations
10:13 Simple pendulum example
12:03 Sneak peak of next lecture
This video shows how to derive the equations of motion for a fully nonlinear system, the particle in a potential well, from F=ma or from Lagrangian mechanics. We will linearize these equations and draw phase portraits to gain intuition about nonlinear systems.
Playlist: youtube.com/playlist?list=PLMrJAkhIeNNTYaOnVI3QpH7jgULnAmvPA
Course Website: http://faculty.washington.edu/sbrunton/me564/
@eigensteve on Twitter
eigensteve.com
databookuw.com
This video was produced at the University of Washington
%%% CHAPTERS %%%
0:00 Problem setup and equations of motion
5:37 Alternative derivation from Euler-Lagrange equations
10:13 Simple pendulum example
12:03 Sneak peak of next lecture
![Python Symbolic Regression (PySR) [Physics Informed Machine Learning]](https://i.ytimg.com/vi/df43V4OjMVs/mqdefault.jpg "Python Symbolic Regression (PySR) [Physics Informed Machine Learning]
This video was produced at the University of Washington, and we acknowledge funding support from the Boeing Company
%%% CHAPTERS %%%
00:00 Intro
02:14 What is Symbolic Regression?
04:08 High-Level Algorithm/ Genetic Programming Overview
// 05:26 Crossover and Mutation
08:12 History of Symbolic Discovery/ Background: Symbolic Discovery
// 09:16 Symbolic Discovery Case Study
// 11:15 Case Study: Control Laws
12:18 Why PySR
// 12:18 PySR: Features
// 13:15 PySR: Benchmarks
// 14:00 PySR: Code Structure
14:19 Why Symbolic Regression/ Potential Outro
15:48 Outro")
