Data-Driven Control: Balanced Truncation and BPOD Example

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

Manipulating Aerodynamic Coefficients

In this video we discuss some potential problems you may encounter when attempting to perform operations with dimensionless aerodynamic coefficients such as ...

Introductory course on aerial robotics, University of Pennsylvania

This course exposes you to the mechanics, design, control, and planning of robotic flight in 3 dimensional environments for micro-aerial vehicles, with an emphasis on quadrotors.

Routh-Hurwitz Criterion, An Introduction

This video gives an introduction into the Routh-Hurwitz Criterion and the Routh Array. I also present a little background information in order to emphasize why the method was developed and...

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...

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...

Peter Ponders PID-Fuzzy Logic vs PID

There are many academic and engineering papers showing how good fuzzy logic control is relative to PID control. Every FL vs PID paper I have seen compares...

Extremum Seeking Control: Challenging Example

This lecture explores the use of extremum-seeking control (ESC) to solve a challenging control problem with a right-half plane zero.

Using Root Locus to Meet Performance Requirements

In this video we investigate how to use the root locus technique to design a controller that meets certain performance specifications.Topics and timestamps:(...

Peter Ponders PID - T0P1 Part 4, Misc Topics

This video covers another way to compute symbolic gains, the difference between having the P gain act on the error or just the feedback, extending bandwidt...

Fourier Series: Part 1

This video will show how to approximate a function with a Fourier series, which is an infinite sum of sines and cosines. We will discuss how these sines and cosines form a basis for the...

Time domain - tutorial 3: signal transformations

In this video, we learn how different transformations can change the signal shape. Specifically, we cover time shifting & scaling as well as amplitude shift...

What Is a Control System and Why Should I Care? (Part 1)

This talk introduces the basic concepts of feedback with lots of visual examples. 

Frequency domain – tutorial 7: Fourier transform examples marathon

In this video, we solve lots of lots examples to practice how to quickly find Fourier transform using table of pairs and properties. The learning objective i...

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.

Linear Systems of Equations

This video describes linear systems of equations and when they have solutions.

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 ...

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...

SVD: Eigenfaces 1 [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 1).

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

Feedforward Control Intro

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

Stability and Eigenvalues [Control Bootcamp]

Here we discuss the stability of a linear system (in continuous-time or discrete-time) in terms of eigenvalues. Later, we will actively modify these eigenvalues, and hence the dynamics...

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...

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.

Direct Synthesis for PID Design Intro

Direct Synthesis for PID Design Intro