Trimming a Model of a Dynamic System Using Numerical Optimization

In this video we show how to find a trim point of a dynamic system using numerical optimization techniques. We generate a cost function that corresponds to a straight and level flight...

Data-Driven Control: Change of Variables in Control Systems (Correction)

This video corrects a typo in the previous lecture.

Complex Fourier Series

This video will describe how the Fourier Series can be written efficiently in complex variables.

SVD: Eigenfaces 3 [Python]

This video describes how the singular value decomposition (SVD) can be used to efficiently represent human faces, in the so-called "eigenfaces" (Python code, part 3).

Simulating the Lorenz System in Matlab

This video shows how simple it is to simulate dynamical systems, such as the Lorenz system, in Matlab, using ode45.

Controls Engineering in the FIRST Robotics Competition

This guide is intended to make an advanced engineering topic approachable so it can be applied by those who aren’t experts in control theory. The intended audience is high school students...

Stanford CS234: Reinforcement Learning | Winter 2019 | Lecture 7 - Imitation...

Professor Emma Brunskill

Assistant Professor, Computer Science

Stanford AI for Human Impact Lab

Stanford Artificial Intelligence Lab

Statistical Machine Learning Group

Data-Driven Control: Error Bounds for Balanced Truncation

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

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...

Unitary Transformations and the SVD [Matlab]

This video describes how the singular value decomposition (SVD) is related to unitary transformations, with Matlab code.

Stanford CS234: Reinforcement Learning | Winter 2019 | Lecture 5 - Value Fun...

Professor Emma Brunskill

Assistant Professor, Computer Science

Stanford AI for Human Impact Lab

Stanford Artificial Intelligence Lab

Statistical Machine Learning Group

RL Course by David Silver - Lecture 3: Planning by Dynamic Programming

Introduces policy evaluation and iteration, value iteration, extensions to dynamic programming and contraction mapping.

Override and Reset Feedback

Override (Select, Safety, Switch) control observes an auxiliary variable and takes over from the primary controller when a limit is exceeded.  Reset feedback is a method to prevent the non...

Data-Driven Control: Balanced Truncation and BPOD Example

In this lecture, we explore balanced truncation and BPOD on a numerical example in Matlab.

Velocity & Acceleration in Non-Inertial Reference Frames (Coriolis &...

In this video we derive a mathematical description of velocity and acceleration in non-inertial reference frame. We examine the effect of fictitious forces that are witnessed by observers on...

Sliding Mode Control Design for a Robotic Manipulator

This MATLAB/Simulink example shows how to design a controller for a robotic manipulator with two actuated joints using sliding mode control (SMC). SMC is useful for systems that require...

Singular Value Decomposition (SVD): Dominant Correlations

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

SVD: Eigen Action Heros [Matlab]

This video describes how the singular value decomposition (SVD) can be used to efficiently represent human faces. In this example, we represent action heros (Matlab).

Linear Regression 3 [Python]

This video describes how the singular value decomposition (SVD) can be used for linear regression in Python (part 3).

Bode Plot Drawing Tool

This page demonstrates the techniques described previously to take a transfer function defined by the user, identify the constituent terms, draw the individual Bode plots, and then combine...

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...

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

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

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

Moving Average Filter - Theory and Software Implementation

Moving average filter theory (time domain, frequency domain, Z-transform, FIR, etc..) and software implementation on a real-time embedded system using an STM32 microcontroller and a...

Numerically Linearizing a Dynamic System

In this video we show how to linearize a dynamic system using numerical techniques. In other words, the linearization process does not require an analytical description of the system. This...