
Extremum 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 MoreBut what is the Fourier Transform? A visual introduction.
An animated introduction to the Fourier Transform.
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 MoreLearning From Data
This is an introductory course in machine learning (ML) that covers the basic theory, algorithms, and applications. ML is a key technology in Big Data, and in many financial, medical...
See MoreRADAR Engineering
Radar technology is used widely today. The principles involved are very fundamental and every engineering student studies them at least once. This playlist covers Radar Engineering for an EE...
See MoreAdvances in Feedforward Control for Measurable Disturbances (slides)
These slides present several contributions to improve the feedforward control approaches when inversion problem arise: the ideal compensator may not be realizable due to negative delay...
See MoreVibrational Control in Insect Flight
Abstract: It is generally accepted among biology and engineering communities that insects are unstable at hover. However, existing approaches that rely on direct averaging do not fully...
See MoreMatlab Radar Designer App
The Radar Designer app is an interactive tool that assists engineers and system analysts with high-level design and assessment of radar systems at the early stage of radar development. Using...
See MoreModel predictive control python toolbox
do-mpc is a comprehensive open-source toolbox for robust model predictive control (MPC) and moving horizon estimation (MHE). do-mpc enables the efficient formulation and solution of control...
See MoreITCRI: An Interactive Software Tool for Control-Relevant Identification
The Interactive Tool for Control Relevant Identification (ITCRI) comprehensively captures the control-relevant identification process, from input design to closed-loop control, depicting...
See MoreFixed-Point HDL-Optimized Minimum-Variance Distortionless-Response (MVDR) Be...
This example shows how to implement a fixed-point HDL-optimized minimum-variance distortionless-response (MVDR) beamformer in MATLAB.
See MoreBlock Diagram Algebra
In this video we introduce block diagrams (AKA signal flow diagrams). We explore how they are used to describe complex systems as well as how to perform blo...
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 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 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 MoreWhy Choose Model-Based Reinforcement Learning?
What is the difference between model-free and model-based reinforcement learning? Explore the differences and results as the learning models are applied to balancing a cart/pole system as an...
See MoreSystem 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 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 MoreImproving the Beginner's PID - Introduction
In conjunction with the release of the new Arduino PID Library Brett has released this series of posts that explain his PID code. He start's with what he call's “The Beginner’s PID.” He...
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 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 MoreMATLAB Example: Train MBPO Agent to Balance Cart-Pole System
This example shows how to train a model-based policy optimization (MBPO) agent to balance a cart-pole system modeled in MATLAB. For more information on MBPO agents, see Model-Based Policy...
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 #6: z-plane warping and the bilinear transform
We’re continuing our journey through discrete control and in this video, we’re going to expand our understanding of the bilinear transform. Along the way, we’ll learn about how this...
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