Sparse Identification of Nonlinear Dynamics for Model Predictive Control

This lecture shows how to use sparse identification of nonlinear dynamics with control (SINDYc) with model predictive control to control nonlinear systems purely from data.

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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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State Space in Process Control

An overview on how we can derive a state space model from a given set of state variables and inputs, as well as an intro to deviation variables. This is part...

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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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Data Preprocessing and the Short-Time Fourier Transform | Deep Learning for ...

Data in its raw form might not be ideal for training a network. There are some changes we can make to the data that are often desired or sometimes necessary in order to make training faster...

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Data-Driven Control: ERA and the Discrete-Time Impulse Response

In this lecture, we describe how the discrete-time impulse response is used in the eigensystem realization algorithm (ERA).

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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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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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Drone Simulation and Control, Part 2: How Do You Get a Drone to Hover?

In the last video, we showed we can manipulate the four motors of a quadcopter to maneuver it in 3D space by getting it to roll, pitch, yaw, and change its thrust. We also covered the four...

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Designing a PID Controller Using the Ziegler-Nichols Method

In this video we discuss how to use the Ziegler-Nichols method to choose PID controller gains. In addition to discussing the method and providing a Matlab i...

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Peter 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...

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Fourier Analysis: Overview

This video presents an overview of the Fourier Transform, which is one of the most important transformations in all of mathematical physics and engineering. This series will introduce the...

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Derivation of Rodrigues’ Rotation Formula

In this video we explain and derive Rodrigues’ Rotation Formula. This functions describes how to rotate an arbitrary vector about another arbitrary axis of ...

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Using 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...

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Lecture 4: Electromechanical system Transfer functions and Analogous circuit...

The transfer function of a dc motor driving a mechanical load [an electromechanical system] has been derived following which a quarter car model is discussed... See More

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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Designing a Lead Compensator with Root Locus

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

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Frequency domain – tutorial 12: FT of periodic signals

In this video, we learn how to find the Fourier transform for periodic signals. The following materials are covered:1) relation between Fourier transform and...

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Linear Quadratic Regulator (LQR) Control for the Inverted Pendulum on a Cart...

Here we design an optimal full-state feedback controller for the inverted pendulum on a cart example using the linear quadratic regulator (LQR). In Matlab, we find that this is a simple one...

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Lecture 7: More on Signal Flow Graphs and Block Diagram Reduction

In this video lesson, extra problems on SFGs are considered, how to obtain an SFG from a block diagram is explained with the help of armature controlled dc m... See More

Stanford CS234: Reinforcement Learning | Winter 2019 | Lecture 8 - Policy Gr...

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: Genetic Programming Control

This lecture discusses the use of genetic programming to manipulate turbulent fluid dynamics in experimental flow control.

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Lectures on Adaptive Control and Learning by Tansel Yucelen

A serie of lectures on the topic of adaptive controllers.

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Transfer Functions in Simulink for Process Control

An introduction on deriving transfer functions from a linearized state space model via Laplace Transforms, and how we can input transfer functions into Simul...

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RL Course by David Silver - Lecture 2: Markov Decision Process

Explores Markov Processes including reward processes, decision processes and extensions.

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