
Type
Experience
Scope
Koopman 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 MoreWhat Is Fuzzy Logic | Fuzzy Logic Part 1
This video introduces fuzzy logic and explains how you can use it to design a fuzzy inference system (FIS), which is a powerful way to use human experience to design complex systems...
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...
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 MoreGuaranteed Margins for LQR Regulators
John Doyle's famous paper! He presents a counterexample that shows that are no guaranteed margins for LQG systems.
See MoreMATLAB Function: phased.MVDRBeamformer
The phased.MVDRBeamformer System object™ implements a narrowband minimum-variance distortionless-response (MVDR) beamformer. The MVDR beamformer is also called the Capon beamformer. An MVDR...
See MoreManuscript about ITISE: an Interactive Software Tool for System Identificati...
The paper describes the conceptual basis, main features and functionality of an interactive software tool developed in support of system identification education and discovery.
This...
See MoreThe Institute for Systems Theory and Automatic Control MATLAB Apps
The Institute for Systems Theory and Automatic Control offers 5 Matlab Apps on the topics of the Nyquist Criterion, Robustness and Stability, Loopshaping, Controllability and Observability...
See MoreMATLAB Example: Fault Detection Using an Extended Kalman Filter
This example shows how to use an extended Kalman filter for fault detection. The example uses an extended Kalman filter for online estimation of the friction of a simple DC motor...
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 MoreMIMO Radar: TI Application Report
MIMO radar is a key technology in improving the angle resolution (spatial resolution) of mmwave-radars. This article introduces the basic principles of the MIMO-radar and the different...
See MoreNyquist Stability Criterion, Part 1
An explanation of the Nyquist Stability Criterion. This video steps through the importance of the criterion, how to interpret the Nyquist plot graphically, and why it is the way it is....
See MoreArtificial Intelligence
This lecture discusses artificial intelligence (AI) in the context of data science and machine learning.
See MoreControl Systems in Practice, Part 4: Why Time Delay Matters
Time delays exist in two varieties: signal distorting delays, like phase lag, in which each frequency is delayed by a different amount of time, resulting in a distorted signal shape; and non...
See MoreDiscrete control #2: Discretize! Going from continuous to discrete domain
This is the second video in the discrete control series. It focuses on discretizing a continuous system - getting to the z-domain from the s-domain.
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 MoreUnderstanding Control Systems: The Disturbance Rejection Problem
This video provides a demonstration using a car to show how you can simulate open- and closed-loop systems in Simulink®.
First, you will learn how to model and tune open-loop systems. The...
See MoreA real control system - how to start designing
Let’s design a control system the way you might approach it in a real situation rather than an academic one. In this video, I step through a control problem and show how control theory is...
See MoreHow Kalman Filters Work, Part 1
This article looks at four popular estimation filter architectures: particle filter, sigma point filter, extended Kalman filter, and the Kalman filter. It discusses how all four of these...
See MoreThoughts on Furthering the Control Education of Practicing Engineers
This paper was presented at the 2019 IFAC Advances on Control Education Conference (IFAC-ACE), Philadelphia, PA, USA, July 7-9, 2019, and is in the conference proceedings. This paper aims to...
See MoreSystems Engineering, Part 1: What Is Systems Engineering?
This video covers what systems engineering is and why it’s useful. We will present a broad overview of how systems engineering helps us develop complex projects that meet the program...
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 MoreHow Simulations Work
This article sets out the critical aspects of building good simulations — that is, simulations that are accurate, easy to develop and analyze, and fast. The first sections deal with how a...
See MoreITSIE: An Interactive Software Tool for System Identification Education
ITSIE is an Interactive Tool for System Identification Education. The tool is developed using Sysquake, a Matlab-like language with fast execution and excellent facilities for interactive...
See MoreBut what is the Fourier Transform? A visual introduction.
An animated introduction to the Fourier Transform.
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