
CORRECTION: Bode Plots by Hand: Complex Poles or Zeros
I explain how to determine the straight-line estimate of the Bode Plot for a second order transfer function with a pair of complex poles. This video is a repeat of the last half of the Bode...
See MoreA Visual Introduction to Machine Learning
Machine Learning Explained in interactive visualizations (part 1).
See MorePeter Ponders PID - Controlling an Under Damp Mass and Spring System
Demonstrates:How to calculate the PID gains. The importance of the derivative gain. How to simulate the mass and spring systemControl limitations based on s...
See MoreHeat Transfer Demonstration
In this video we demonstrate heat transfer through a metal bar. By heating one side of the bar we can impose a non-uniform temperature distribution across t...
See MoreData-Driven Control: Balanced Models with ERA
In this lecture, we connect the eigensystem realization algorithm (ERA) to balanced proper orthogonal decomposition (BPOD). In particular, if enough data is collected, then ERA produces...
See MoreMachine Learning Control: Genetic Programming
This lecture explores the use of genetic programming to simultaneously optimize the structure and parameters of an effective control law.
See MoreNumerically 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...
See MorePeter Ponders PID - Why PID with 2nd Derivative Gain?
If you have ever tuned a hydraulic system and wondered why PID control didn't work better than PI control the answer is here. Since the 1980s people have kn...
See MoreFrequency 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...
See MoreData-Driven Control: Observer Kalman Filter Identification
In this lecture, we introduce the observer Kalman filter identification (OKID) algorithm. OKID takes natural input--output data from a system and estimates the impulse response, for later...
See MoreUnderstanding Model Predictive Control, Part 4: Adaptive, Gain-Scheduled and...
This video explains the type of MPC controller you can use based on your plant model, constraints, and cost function. An optimization problem with these properties is a convex one, and you...
See MoreDesign of Embedded Robust Control Systems Using MATLAB®/Simulink®
Robust control theory allows for changes in a system whilst maintaining stability and performance. Applications of this technique are very important for dependable embedded systems, making...
See MoreTikZ source Code: RL Series
TikZ source Code for RL Series.
See MoreTime 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...
See MoreDrone Simulation and Control, Part 3: How to Build the Flight Code
This video describes how to create quadcopter flight software from the control architecture developed in the last video. It covers how to process the raw sensor readings and use them with...
See MoredRehmFlight VTOL - Teensy (Arduino) Flight Controller and Stabilization
dRehmFlight VTOL is a new flight controller and stabilization package intended to be used for small to medium sized hobby or research projects. dRehmFlight is the code, and the physical...
See MoreInputs and Outputs as defined by a Process Control Engineer
Defining process inputs and outputs is a lot more complicated than I initially thought when I was learning about process control. In this video, I share how ...
See MoreTikZ source Code: matlab2tikz example
TikZ source Code: matlab2tikz example
See MoreStanford CS234: Reinforcement Learning | Winter 2019 | Lecture 4 - Model Fre...
Professor Emma Brunskill
Assistant Professor, Computer Science
Stanford AI for Human Impact Lab
Stanford Artificial Intelligence Lab
Statistical Machine Learning Group
Final Value Theorem and Steady State Error
This Final Value Theorem is a way we can determine what value the time domain function approaches at infinity but from the S-domain transfer function. This is very helpful when we're trying...
See MoreRL Course by David Silver - Lecture 10: Classic Games
An overview of Game Theory, minimax search, self-play and imperfect information games.
See MoreSolving the Heat Equation with the Fourier Transform
This video describes how the Fourier Transform can be used to solve the heat equation. In fact, the Fourier transform is a change of coordinates into the eigenvector coordinates for the...
See MoreState Space Representation of Differential Equations
In this video we show how to represent differential equations (either linear or non-linear) in state space form. This is useful as it allows us to combine an...
See MoreDesigning a Lag Compensator with Root Locus
This video walks through a phase lag compensator example using the Root Locus method.
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