
Z-Transform - Practical Applications
Covering practical applications of the Z-transform used in digital signal processing, for example, stability analysis and frequency response of discrete-time systems. Theory, C code, and...
See MoreAdvances in feedforward control for measurable disturbances
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 MoreKalman Filter Virtual Lab
The Kalman Filter virtual laboratory contains interactive exercises that let you study linear and extended Kalman filter design for state estimation of a simple pendulum system. The virtual...
See MoreVirtual Labs for control education
This resource provides different links to virtual and remote labs that can be used for control education. Virtual and remote labs are very powerful tools for learning and teaching, that...
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 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 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 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 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 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 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 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 MoreSystem Identification: Dynamic Mode Decomposition with Control
This lecture provides an overview of dynamic mode decomposition with control (DMDc) for full-state system identification. DMDc is a least-squares regression technique based on the singular...
See MoreOnline Fault Detection for a DC Motor
Program embedded processors to estimate parameters and detect changes in motor dynamics in real time using System Identification Toolbox™.
See MoreWhy the Riccati Equation Is important for LQR Control
This Tech Talk looks at an optimal controller called linear quadratic regulator, or LQR, and shows why the Riccati equation plays such an important role in solving it efficiently. The talk...
See MoreNathan Kutz:"Data-driven Discovery of Governing Physical Laws"
Seminar by Dr.Nathan Kutz on "Data-driven Discovery of Governing Physical Laws" on 10/31/2018 CICS Seminar Series
See MoreGeodetic Coordinates: Computing Latitude and Longitude
In this video we show how to compute the geodetic latitude and terrestrial longitude if given the velocity north and east. This is useful for simulating a body moving over a spheroid Earth...
See MoreKoopman Spectral Analysis (Continuous Spectrum)
In this video, we discuss how to use Koopman theory for dynamical systems with a continuous eigenvalue spectrum. These systems are quite common, such as a pendulum, where the period...
See MorePrincipal Component Analysis (PCA) 1 [Python]
This video describes how the singular value decomposition (SVD) can be used for principal component analysis (PCA) in Python (part 1).
See MorePID Controller Implementation in Software
How to implement a PID controller in software using C, discussing theory and practical considerations. Demonstration of PID controller code using a custom flight simulator.
See MoreBridging the Gap: Using Real World Problems to Unveil Deep Control Principle...
This is a plenary lecture given at the 2020 IEEE Conference on Control Systems Technology, Montreal, Canada, August 24-26, 2020. There is no paper, but this is the video of the talk.
See MoreSystem Identification: DMD Control Example
This lecture gives a Matlab example of dynamic mode decomposition with control (DMDc) for full-state system identification.
See MoreKristin Pettersen Lectures on Nonlinear Control
Kristin Pettersen Lectures on Nonlinear Control, including many of the necessary mathematical tools and concepts.
See MoreHow Antennas Work
Antennas constitute as a major component in various communication systems, signal transmission and many others. It is important to understand how they work and create propagating waves in...
See MoreReal-Time Software Implementation of Analog Filters
Modelling analog filters, discretisation, and implementation of the digitally-equivalent filters on a real-time, embedded system (STM32). Includes theory, DSP, firmware, and results.
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