Adaptive control

Fuzzy control of inverted pendulum

Fuzzy control of inverted pendulum, State-feedback controller is designed based on T-S fuzzy model with the consideration of system stability and performance.

From playlist Demonstrations

Adaptive Control Basics: What Is Model Reference Adaptive Control?

Use an adaptive control method called model reference adaptive control (MRAC). This controller can adapt in real time to variations and uncertainty in the system that is being controlled. See how model reference adaptive control cancels out the unmodelled dynamics so that a nominal plant

From playlist Learning-Based Control

What Is Feedforward Control? | Control Systems in Practice

A control system has two main goals: get the system to track a setpoint, and reject disturbances. Feedback control is pretty powerful for this, but this video shows how feedforward control can make achieving those goals easier. Temperature Control in a Heat Exchange Example: http://bit.ly

From playlist Control Systems in Practice

What Is Gain Scheduling? | Control Systems in Practice

Often, the best control system is the simplest. When the system you’re trying to control is highly nonlinear, this can lead to very complex controllers. This video continues our discussion on control systems in practice by talking about a simple form of nonlinear control: gain scheduling.

From playlist Control Systems in Practice

How To Build User-Adaptive Interfaces

Users have indicated many preferences on their devices these days. They want the operating system and apps to look and feel like their own. User-adaptive interfaces are those which are ready to use these preferences to enhance the user experience, to make it feel more at home. If done corr

From playlist Web Design: CSS / SVG

Fuzzy control of inverted pendulum,

Fuzzy control of inverted pendulum, State-feedback controller is designed based on T-S fuzzy model with the consideration of system stability and performance. Details can be found in https://nms.kcl.ac.uk/hk.lam/HKLam/index.php/demonstrations

From playlist Demonstrations

Everything You Need to Know About Control Theory

Control theory is a mathematical framework that gives us the tools to develop autonomous systems. Walk through all the different aspects of control theory that you need to know. Some of the concepts that are covered include: - The difference between open-loop and closed-loop control - How

From playlist Control Systems in Practice

The Explainer: Balancing Execution and Adaptation

Most organizations only focus on execution or adaptation. But both are important for success. Research shows that most leaders and organizations tend to focus on just one type of performance. But there are two types that are important for success. The first type is known as tactical perf

From playlist The Explainer

Understanding Control Systems, Part 2: Feedback Control Systems

Explore introductory examples to learn about the basics of feedback control (closed-loop control) systems. Learn how feedback control is used to automate processes and discover how it deals with system variations and unexpected environmental changes. The examples utilize everyday applian

From playlist Understanding Control Systems

Adaptive Model Predictive Control Design with Simulink | Understanding MPC, Part 7

In this video, you will learn how to design an adaptive Model Predictive Control controller for an autonomous steering vehicle system whose dynamics change with respect to the longitudinal velocity. - Free Technical paper on Adaptive Cruise Controller with Model Predictive Control: http:/

From playlist Understanding Model Predictive Control

Control System Design with MATLAB and Simulink

Watch live as Siddharth Jawahar and Arkadiy Turevskiy walk through systematically designing controllers in Simulink using Simulink Control Design. Simulink Control Design lets you design and analyze controllers in Simulink. You will learn how you can automatically tune arbitrary SISO and

From playlist MATLAB and Simulink Livestreams

Adaptive, Gain-Scheduled and Nonlinear Model Predictive Control | Understanding MPC, Part 4

This video explains the type of MPC controller you can use based on your plant model, constraints, and cost function. - Model Predictive Control Toolbox: http://bit.ly/2xgwWvN- - What Is Model Predictive Control Toolbox?: http://bit.ly/2xfEe2M The available options include the linear ti

From playlist Understanding Model Predictive Control

High-order Homogenization in Optimal Control by the Bloch Wave Method by Agnes Lamacz-Keymling

DISCUSSION MEETING Multi-Scale Analysis: Thematic Lectures and Meeting (MATHLEC-2021, ONLINE) ORGANIZERS: Patrizia Donato (University of Rouen Normandie, France), Antonio Gaudiello (Università degli Studi di Napoli Federico II, Italy), Editha Jose (University of the Philippines Los Baño

From playlist Multi-scale Analysis: Thematic Lectures And Meeting (MATHLEC-2021) (ONLINE)

Angela Schoellig: "Machine Learning for Robotics: Achieving Safety, Performance and Reliability..."

Intersections between Control, Learning and Optimization 2020 "Machine Learning for Robotics: Achieving Safety, Performance and Reliability by Combining Models and Data in a Closed-Loop System Architecture" Angela Schoellig - University of Toronto Abstract: The ultimate promise of roboti

From playlist Intersections between Control, Learning and Optimization 2020

The Clean Architecture

What is the clean architecture and how you would build one in .NET? Recently Bob Martin has categorized a set of architectures, including hexagonal architecture, onion architecture and screaming architecture as 'the clean architecture' - a layered architecture of concentric circles with a

From playlist Software Development

Lec 18 | MIT 2.830J Control of Manufacturing Processes, S08

Lecture 18: Sequential experimentation: Experimentation and Robust Design and Engineering Systems. (Courtesy of Dan Frey. Used with permission.) Instructor: Duane Boning, David Hardt View the complete course at: http://ocw.mit.edu/2-830JS08 License: Creative Commons BY-NC-SA Mor

From playlist MIT 2.830J, Control of Manufacturing Processes S08

DDPS | Towards reliable, efficient, and automated model reduction of parametrized nonlinear PDEs

Description: Many engineering tasks, such as parametric study and uncertainty quantification, require rapid and reliable solution of partial differential equations (PDEs) for many different configurations. In this talk, we consider goal-oriented model reduction of parametrized nonlinear PD

From playlist Data-driven Physical Simulations (DDPS) Seminar Series

Symmetry and Adaptation in C. Elegans Response to Touch - Massimo Vergassola

2015 Joshua Lederberg - John von Neumann Symposium "Towards Quantitative Biology" Massimo Vergassola University of California, San Diego December 2, 2015

From playlist Joshua Lederberg - John von Neumann Symposium

What Is PID Control? | Understanding PID Control, Part 1

Chances are you’ve interacted with something that uses a form of this control law, even if you weren’t aware of it. That’s why it is worth learning a bit more about what this control law is, and how it helps. PID is just one form of feedback controller. It is the simplest type of contro

From playlist Understanding PID Control