Linear Regression 2 [Python]

This video describes how the singular value decomposition (SVD) can be used for linear regression in Python (part 2).

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Stanford CS234: Reinforcement Learning | Winter 2019 | Lecture 11 - Fast Rei...

Professor Emma Brunskill
Assistant Professor, Computer Science
Stanford AI for Human Impact Lab
Stanford Artificial Intelligence Lab
Statistical Machine Learning Group

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Machine Learning Control: Tuning a PID Controller with Genetic Algorithms

This lecture shows how to use genetic algorithms to tune the parameters of a PID controller. Tuning a PID controller with genetic algorithms is not generally recommended, but is used to...

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Laplace Transforms to Derive Transfer Functions

Once we have a state space model, we will take a Laplace Transform to derive the transfer function to determine the response of an output relative to an inpu...

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Control System with MATLAB - Block Diagram Reduction

Carrying out block reduction using MATLAB has been explained in this video See More

Understanding Model Predictive Control, Part 7: Adaptive MPC Design with Sim...

In this video, you will learn how to design an adaptive MPC controller for an autonomous steering vehicle system whose dynamics change with respect to the longitudinal velocity. After you...

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Stability of Closed Loop Control Systems

This video explains why we need design tools like the Routh-Hurwitz Criterion, Bode Plots, Nyquist Plots, and Root Locus. This is an introduction into the difficulties of determining the...

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Direct Synthesis for PID Controller Design

What tuning parameters should you choose for your controller? The Direct Synthesis Model is one method control engineers use today to evaluate controller par...

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Designing a Lag Compensator with Root Locus

This video walks through a phase lag compensator example using the Root Locus method.

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Fuzzy Inference System Walkthrough | Fuzzy Logic Part 2

This video walks step-by-step through a fuzzy inference system. Learn about concepts like membership function shapes, fuzzy operators, multiple-input inference systems, and rule firing...

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Simple Examples of PID Control

In this video I continue the topic of PID control. We walk through a simple control system and visualize how each of the three paths, P, I, and D, all address specific problems that arise...

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Reachability and Controllability with Cayley-Hamilton [Control Bootcamp]

Here we use the Cayley-Hamilton Theorem to show that the full state space is reachable if and only if the system is controllable.

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State 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...

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Tuning a Fuzzy Logic Controller with Data | Fuzzy Logic, Part 4

This video covers the basics of data-driven approaches to tuning fuzzy inference systems. See what it means to find an optimal solution, which fuzzy inference parameters are being tuned...

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

This video corrects a typo in the previous lecture.

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Computing Euler Angles: The Euler Kinematical Equations and Poisson’s Kinema...

In this video we discuss how the time rate of change of the Euler angles are related to the angular velocity vector of the vehicle. This allows us to design...

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MIT 6.S191: Introduction to Deep Learning

MIT's introductory course on deep learning methods with applications to computer vision, natural language processing, biology, and more! Students will gain foundational knowledge of deep...

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Sketching Root Locus Part 2

This is the second part of how to sketch a root locus by hand. However instead of following the normal rules for sketching a locus that you'd see in a book, I decided to explain the rules...

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Discrete control #5: The bilinear transform

This is video number five on discrete control and here, we’re going to cover the famous and useful bilinear transform. The bilinear transform is yet another method for converting, or mapping...

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Bandwidth of a Dynamic System

In this video we discuss the definition and physical meaning of the bandwidth of a dynamic system. We’ll see that this is a performance metric that is used ...

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Peter 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...

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Control Bootcamp: Benefits of Feedback on Cruise Control Example

Here we investigate the benefits of feedback for systems with uncertain dynamics and disturbances, as illustrated on a cruise control example.

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Solving the 1D Wave Equation

In this video, we solve the 1D wave equation. We utilize the separation of variables method to solve this 2nd order, linear, homogeneous, partial differenti...

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Laplace domain – tutorial 1: Laplace transform

In this video, we learn about Laplace transform which enables us to travel from time to the Laplace domain. The following materials are covered:1) why we nee...

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SVD Method of Snapshots

This video describes how to compute the singular value decomposition (SVD) using the method of snapshots, by Sirovich 1987.

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