
Type
Experience
Scope
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.
See MoreUnderstanding The Sensitivity Function
In this video I explain the sensitivity function and try to demystify the equation used to solve for the nominal sensitivity peak. Sensitivity describes how much process variations affect...
See MoreRandomized SVD: Power Iterations and Oversampling
This video discusses the randomized SVD and how to make it more accurate with power iterations (multiple passes through the data matrix) and oversampling.
See MoreUsing 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 transfo...
See MoreTikZ source Code: Switching Smooth Filippov
TikZ source Code: Switching Smooth Filippov
See MoreData-Driven Control: Change of Variables in Control Systems (Correction)
This video corrects a typo in the previous lecture.
See MoreSVD: Image Compression [Matlab]
This video describes how to use the singular value decomposition (SVD) for image compression in Matlab.
See MoreDesigning 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...
See MoreDiscrete 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...
See MoreLinear Regression 1 [Matlab]
This video describes how the singular value decomposition (SVD) can be used for linear regression in Matlab (part 1).
See MoreTransfer Functions: Introduction and Implementation
In this video we introduce transfer functions and show how they can be derived from a set of linear, ordinary differential equations. We also examine how to...
See MoreExtremum Seeking Control in Simulink
This lecture explores extremum-seeking control (ESC) on a simple example in Matlab’s Simulink.
See MoreDigital 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...
See MoreMachine Learning Control: Genetic Programming Control
This lecture discusses the use of genetic programming to manipulate turbulent fluid dynamics in experimental flow control.
See MoreIntroduction to Partial Differential Equations
This is the first lesson in a multi-video discussion focused on partial differential equations (PDEs).In this video we introduce PDEs and compare them with o...
See MoreApollo's Flight Computer: Epitome of Engineering
The Apollo missions' success can be vastly accredited to the success of building a robust, one-of-a-kind flight computer for its guidance, navigation and control. Follow this video to...
See MoreFourier Series and Gibbs Phenomena [Python]
This video will describe how to compute the Fourier Series in Python and Gibbs Phenomena that appear for discontinuous functions.
See MoreUnderstanding 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...
See MoreComputing 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 an algorithm to consume...
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