
Machine 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 MoreFrequency domain – tutorial 5: Fourier transform
In this video, we learn about Fourier transform which enables us to travel from time to frequency domain when a signal is not periodic. The learning objectiv...
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 MoreIntroduction to System Stability and Control
This video attempts to provide an intuitive understanding of concepts like stability and stability margin. I briefly describe both of these topics with examples and explain how you can...
See MoreUnitary Transformations and the SVD [Python]
This video describes how the singular value decomposition (SVD) is related to unitary transformations, with Python code.
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 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
Controllability, Reachability, and Eigenvalue Placement [Control Bootcamp]
This lecture explains the equivalence of controllability, reachability, and the ability to arbitrarily place eigenvalues of the closed loop system.
See MoreRL Course by David Silver - Lecture 10: Classic Games
An overview of Game Theory, minimax search, self-play and imperfect information games.
See MoreTransfer Function to State Space
In this video we show how to transform a transfer function to an equivalent state space representation. We will derive various transformations such as contr...
See MoreMoving 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...
See MoreData-Driven Control: BPOD and Output Projection
In this lecture, we introduce the output projection for balancing proper orthogonal decomposition (BPOD), to reduce the number of adjoint simulations required when the number of measurements...
See MoreManipulating Aerodynamic Coefficients
In this video we discuss some potential problems you may encounter when attempting to perform operations with dimensionless aerodynamic coefficients such as ...
See MoreApollo's Flight Computer: Epitome of Engineering
The Apollo missions' success can be vastly accredited to the success of building a robust, one-of-a-kind flight computer for its guidance, navigation and control. Follow this video to...
See MoreRouth-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...
See MoreUsing 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 transformation matrix which combines a...
See MoreThe 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...
See MorePeter Ponders PID - IAE,ITAE,ISE Performance indicators
Performance indicators can be used to compute closed loop pole locations. Only one gain parameter is required to move the pole locations closer to the origi...
See MoreControl Systems Lectures - Closed Loop Control
This lecture discusses the differences between open loop and closed loop control.
See MoreUsing 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:(...
See MoreAuto Tuning a Small DC Motor in Torque Mode
I was really testing the picture in picture feature of the Screen Flow software I use to make these videos. I knew the auto tuning would work. I kept the v...
See MoreParseval's Theorem
Parseval's theorem is an important result in Fourier analysis that can be used to put guarantees on the accuracy of signal approximation in the Fourier domain.
See MoreTime 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...
See MoreKoopman Spectral Analysis (Multiscale systems)
In this video, we discuss recent applications of data-driven Koopman theory to multi-scale systems.
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