Lecture 26: Stability examples, GM and PM using Nyquist Stability Criterion

This video discusses some numerical examples to show how stability can be determined using Nyquist stability criterion. Also explained is how to calculate ga... See More

Time domain - tutorial 9: convolution examples

In this video, we use a systematic approach to solve lots of examples on convolution. By the end of this lecture, you should be able to find convolution betw...

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What Is a Control System and Why Should I Care? (Part 2)

This talk gives a glimpse of some of the methods and math that allow us to understand feedback systems. Continuing on from Part 1, it gives a description of how we use scientific principles...

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Frequency domain – tutorial 3: filtering (periodic signals)

In this video, we learn about filtering which enables us to manipulate the frequency content of a signal. A common filtering application is to preserve desi...

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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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Posicast Control - 1 ( In English)

This video is an introduction to a learning journey about Posicast Control structured as follows: - Preface - Motivation - Introduction to Posicast Control - Half-Cycle Posicast

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Constraint Enforcement for Improved Safety | Learning-Based Control

Learn about the constraints of your system. Then see a how to enforce those constraints so the system does not violate them. Constraint enforcement is important for safety-critical...

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Least Squares Regression and the SVD

This video describes how the SVD can be used to solve linear systems of equations. In particular, it is possible to solve nonsquare systems (overdetermined or underdetermined) via least...

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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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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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Direct Design Example for PID Controller

I go through an example problem of how we can use Direct Design (also called Direct Synthesis) to determine the tuning parameters for a PID controller, given...

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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...

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Digital Twin Parameter Tuning

Learn how to tune the digital twin model of a pump system to its physical asset using Simulink Design Optimization™. You can use measured data collected from the physical system to tune the...

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Neural Network Architectures

This lecture describes the wide variety of neural network architectures available to solve various problems.

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State Space to Transfer Function

In this video we show how to transform a linear state space representation of a dynamic system to an equivalent transfer function representation. We will de...

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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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Control Bootcamp: Benefits of Feedback on Cruise Control Example (Part 2)

Here we investigate the benefits of feedback for systems with uncertain dynamics and disturbances, as illustrated on a cruise control example. (Part 2)

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Stanford CS229: Machine Learning | Autumn 2018

Autumn 2018 Stanford course on machine learning by Andrew Ng.

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Bode Plots of Complex Transfer Functions

In this video we discuss how to generate a bode plot of a complex transfer function by decomposing it into the individual components. We then show how one c...

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The Fourier Transform and Derivatives

This video describes how the Fourier Transform can be used to accurately and efficiently compute derivatives, with implications for the numerical solution of differential equations.

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Understanding Sensor Fusion and Tracking, Part 2: Fusing a Mag, Accel, and G...

This video describes how we can use a magnetometer, accelerometer, and a gyro to estimate an object’s orientation. The goal is to show how these sensors contribute to the solution, and to...

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Peter Ponders PID, Natural Frequency vs Frequency of Acceleration

This video is intended for servo hydraulic system designers and those that program hydraulic servo systems but it does show how several of the techniques sho...

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Solving the 2D Wave Equation

In this video, we solve the 2D wave equation. We utilize two successive separation of variables to solve this partial differential equation. Topics discuss...

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Lecture 28: Lag Compensator Design using Bode Plots

This video explains how a lag compensator can be designed using Bode plots. A numerical example has also been taken up. See More

Peter Ponders PID - Observers/Estimators

Observers can provide betters estimates of state variables when there is noise and low resolution feed back. This is often necessary to compute the higher d... See More