
Type
Experience
Scope
System Identification: Koopman with Control
This lecture provides an overview of the use of modern Koopman spectral theory for nonlinear control. In particular, we develop control in a coordinate system defined by eigenfunctions of...
See MoreIncreasing Angular Resolution with Virtual Arrays
This MATLAB example introduces how forming a virtual array in MIMO radars can help increase angular resolution. It shows how to simulate a coherent MIMO radar signal processing chain using...
See MoreModel Reference Adaptive Control of Aircraft Undergoing Wing Rock
This example shows how to control roll and roll rate of a delta wing aircraft undergoing wing rock. For this example, the system model is unknown. Therefore, you use model reference adaptive...
See MoreMPCTools: Nonlinear Model Predictive Control Tools for CasADi (Python Interf...
This Python package is a collection of model predictive control tools that build on CasADi by providing a simpler interface. Along with the python package, there are a bunch of example files...
See MoreData-Driven Dynamical Systems Overview
This video provides a high-level overview of this new series on data-driven dynamical systems. In particular, we explore the various challenges in modern dynamical systems, along with...
See MoreExtremum Seeking Control in Matlab
This lecture explores extremum-seeking control (ESC) on a simple example in Matlab. In particular, a discrete-time (digital) version of ESC is coded in a Matlab script.
See MoreWhy Choose Deep Learning? Deep Learning for Engineers, Part 1
This video introduces deep learning from the perspective of solving practical engineering problems. The goal is to provide an introduction to the range of practical engineering problems that...
See MoreControl Systems in Practice, Part 8: The Gang of Six in Control Theory
When analyzing feedback systems, we can get caught up thinking solely about the relationship between the reference signal and the output. However, to fully understand how a feedback system...
See MoreDiscrete control #4: Discretize with the matched method
This is the fourth video on discrete control and in this video we are going to continue exploring the different techniques we can use to discretize a continuous system and talk about the...
See MoreLinear Regression
Linear regression is a cornerstone of data-driven modeling; here we show how the SVD can be used for linear regression.
See MoreMATLAB Function: ztrans
ztrans(f) finds the Z-Transform of f. By default, the independent variable is n and the transformation variable is z. If f does not contain n, ztrans uses symvar.
See MoreAdvances in feedforward control for measurable disturbances (in Spanish)
The efficient compensation of load disturbances is one of the most important tasks in any control system. Most industrial processes are affected by disturbances and only feedback is commonly...
See MoreTrimming and Linearization, Part 1: What is Linearization?
Why go through the trouble of linearizing a model? To paraphrase Richard Feynman, it’s because we know how to solve linear systems. With a linear model we can more easily design a controller...
See MoreNyquist Stability Criterion, Part 2
An explanation of the Nyquist Stability Criterion part 2. This video steps through the how to sketch a Nyquist plot by hand, what to do if there are open loop pools on the imaginary axis...
See MoreRoad Sign Detection using Transfer Learning on RetinaNet
This blog outlines a number of open-source resources for transfer learning that are worthy of exploring, ands show the result of using transfer learning on RetinaNet to develop a road sign...
See MoreRadar Systems Engineering MATLAB Documentation and Examples
The functions in this section give you the MATLAB tools needed to evaluate the performance of a radar system. You can use the radar equation to evaluate the radar received signal-to-noise...
See MoreKalman Filter Simulink 2022A example
This model is intended to help illustrate how a Kalman filter can estimate the state of a system. The "real system" is a nonlinear model of the Temperature Control Lab by Prof. John...
See MoreAlgorithms for Automated Driving
Each chapter of this (mini-)book guides you in programming one important software component for automated driving. Currently, this book contains two chapters: Lane Detection, and Control...
See More3-DOF Orientation Tracking with IMUs
This document is not meant to be a comprehensive review of orientation tracking for virtual reality applications but rather an intuitive introduction to inertial measurement units (IMUs) and...
See MoreNonlinear Model Identification
Mathwork overview page describing nonlinear model identification. Use nonlinear model identification when a linear model does not completely capture your system dynamics. You can identify...
See MoreUnderstanding Closed-Loop Control
This lecture discusses the differences between open loop and closed loop control in a very easy and intuitive way. Daily examples, like a dishwasher, plant irrigation, and car speed systems...
See MoreKoopman Spectral Analysis (Control)
In this video, we explore extensions of Koopman theory for control systems. Much of the excitement and promise of Koopman operator theory is centered around the ability to represent...
See MoreWhy Digital Beamforming Is Useful for Radar
Learn how you can use digital beamformers to improve the performance and functions of radar systems. The MATLAB Tech Talk series on radar covered how to use radar to determine range, range...
See MoreDiscrete control #3: Designing for the zero-order hold
This is the third video on discrete control and in this video, I want to clear up a confusion that I caused last time regarding using the ZOH method to discretize a continuous controller and...
See MoreSystems modeling and representations (French)
Complete course on systems modeling. Includes examples, MATLAB code, and quizzes.
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