Time domain - tutorial 2: signal representation

In this video, we review how to represent information as a signal. The information can be anything such as voice (1D) or an image (2D) or even a video (3D). ...

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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.

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Control Bootcamp: Sensitivity and Robustness

Here we show that peaks in the sensitivity function result in a lack of robustness.

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Internal Model Control Example Problem

I walk through how to design a feedback controller based on a given process transfer function, using Internal Model Control.

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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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Direct Synthesis Method Numerator Dynamics Problem

I walk through how to design a PID feedback controller when given a second order process with numerator dynamics, using the Direct Synthesis Method.

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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...

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Solving 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...

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Frequency Response Analysis FRA and the Amplitude Ratio and Phase Angle

Process engineers model output response to inputs that oscillate via frequency response analysis (FRA). In this video, I'll go over amplitude ratios and phas...

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Peter Ponders PID - Integrated Time Absolute Error - 4 Pole example

This video shows how to calculate the coefficients for a 4 pole ITAE and how to use the 4 pole ITAE to calculate closed loop controller gains.

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Numerically Calculating Partial Derivatives

In this video we discuss how to calculate partial derivatives of a function using numerical techniques. In other words, these partials are calculated withou...

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Peter Ponders PID - FeedForwards - Basics - What they do

The video shows the importance of using feed forwards to reduce error while following a motion profile. See More

Control Systems Lectures - Time and Frequency Domain

This lecture introduces the time and frequency domains. A very quick description of the Laplace Transform is given which will be the base of many of classical control lectures in the future...

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Introduction to Full State Feedback Control

In this video we introduce the concept of a full state feedback controller. We discuss how to use this system to place the eigenvalues of the closed loop sys...

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Control Systems in Practice, Part 6: What Are Non-Minimum Phase Systems?

We like to categorize transfer functions into groups and label them because it helps us understand how a particular system will behave simply by knowing the group that it’s part of. We gain...

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Standing Waves Demonstration

In this video we demonstrate standing waves. We show how the system can be excited by oscillating at specific frequencies to generating standing waves. The...

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Laplace domain – tutorial 4: Laplace transform examples

In this video, we solve lots of examples to practice how to quickly find Laplace transform using the table of pairs & properties and five golden rules on ROC...

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Bode Plots by Hand: Real Constants

This video describes the benefit of being able to approximate a Bode plot by hand and explains what a Bode plot looks like for a simple transfer function; a real constant.

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Frequency domain – tutorial 4: Gibbs phenomenon

In this video, we quickly review the Gibbs phenomenon which involves two facts:1) Fourier sums overshoot at a jump discontinuity2) overshoot does not disapp...

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Why Transfer Functions Matter

Once we know a process's transfer function we can model how it will respond to an variety of inputs very easily, check it out.

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Drone Simulation and Control, Part 4: How to Build a Model for Simulation

This video describes how a good model of the drone and the environment it operates in can be used for simulation and test. It shows how nonlinear and linear models are both needed for...

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Feedforward Control Introduction

I introduce feedforward control (FFC) and describe how it can be used to minimize the difference between an output's setpoint and measured value (the error o...

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Machine Learning - Andrew Ng, Stanford University

Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech...

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Deploying Deep Learning Models | Deep Learning for Engineers, Part 5

This video covers the additional work and considerations you need to think about once you have a deep neural network that can classify your data. We need to consider that the trained network...

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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...

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