
Peter Ponders PID - Cascade Control Part1
I cover whether cascade control is necessary. Why there needs to be a feed back for every loop. How to calculate gains. Bode plots and ratio of the inner t...
See MoreTUTORIAL on Stability and Routh Hurwitz criterion
IMC Design of an Unstable Process Example
In this video, I cover how we can use IMC method to rigorously design a controller for an inherently unstable process (has a positive pole).
See MoreLecture 25: Nyquist stability criterion
Relative Gain Array RGA and Input Output Pairing
The RGA is a tool used by process engineers to determine how to pair inputs and outputs during controller design to strive for better performance and robustn...
See MoreSVD Method of Snapshots
This video describes how to compute the singular value decomposition (SVD) using the method of snapshots, by Sirovich 1987.
See MoreHomogeneous Linear Ordinary Differential Equations
In this video we discuss how to solve homogeneous linear ordinary differential equations (ODEs). The approach outlined in this lecture is applicable to high...
See MoreControl Bootcamp: Loop Shaping Example for Cruise Control
This video demonstrates loop shaping on the cruise control model.
See MoreThe Inverse Laplace Transform
In this video we show how to perform the inverse Laplace transform on a signal in the Laplace domain to obtain its equivalent representation in the time doma...
See MoreBode Plots by Hand: Complex Poles or Zeros
This is a continuation of the Control Systems Lectures. 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...
See MoreSketching 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...
See MoreUnderstanding Model Predictive Control, Part 2: What is MPC?
Learn how model predictive control (MPC) works. Using a simple car example, this video provides insight into an MPC controller’s strategy for finding the optimal steering wheel angle to...
See MoreFinal Value Theorem
In this video we discuss the Final Value Theorem. Given a signal in the Laplace domain, this allows us to predict the steady state value of the signal in th...
See MoreHeat Transfer Demonstration
In this video we demonstrate heat transfer through a metal bar. By heating one side of the bar we can impose a non-uniform temperature distribution across t...
See MoreDrone 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...
See MoreTime domain - tutorial 5: signal properties
In this video, we learn about some special signals which are symmetric around the y-axis (even) or around the origin (odd) . Then we talk about periodic sign...
See MoreIntroduction to the Fourier Transform (Part 1)
This video is an introduction to the Fourier Transform. I try to give a little bit of background into what the transform does and then I go step by step through explaining the Inverse...
See MoreFrequency domain – tutorial 10: modulation
In this video, we learn about modulation technique which is commonly used in communication systems to send information from transmitter to receiver. The foll...
See MorePeter Ponders PID - Closed Loop Zeros
This video covers closed loop zeros, what causes zeros and the benefits and drawbacks of closed loop zeros.
See MoreControl Systems with MATLAB - Time Domain Analysis
Relative Gain Array RGA Analysis
I cover how you can find the relative gain array from the steady state gain array, and interpret the results to determine which input to pair with which outp...
See MorePeter Ponders PID- Motor position control
Lecture 17: Introduction to Compensators/Controllers
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...
See MoreA Visual Introduction to Machine Learning
Machine Learning Explained in interactive visualizations (part 1).
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