Results 21 to 30 of about 1,084,598 (183)

Direct Data Driven Model Reference Control for Flight Simulation Table

IEEE Access, 2022
We present a direct data driven model reference control framework for flight simulation table from both the theoretical analysis and engineering application.
Wang Jianhong, Ricardo A. Ramirez-Mendoza   +1 more
doaj   +3 more sources

pyvrft: A Python package for the Virtual Reference Feedback Tuning, a direct data-driven control method

SoftwareX, 2020
In this paper, the pyvrft, a Python package for the data-driven control method known as Virtual Reference Feedback Tuning (VRFT), is presented. Virtual Reference Feedback Tuning is a control design technique that does not use a mathematical model from ...
Emerson Boeira, Diego Eckhard
doaj   +2 more sources

Auto-tuning of reference models in direct data-driven control

Automatica, 2023
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Masti, Daniele, Breschi, Valentina, Formentin, Simone, Bemporad, Alberto   +3 more
openaire   +3 more sources

Robust direct data-driven control for probabilistic systems [PDF]

Systems & Control Letters, 2023
Published by Elsevier, Amsterdam [u.a.]
Alexander von Rohr, Dmitrii Likhachev, Sebastian Trimpe   +2 more
openaire   +4 more sources

On the Role of Regularization in Direct Data-Driven LQR Control

2022 IEEE 61st Conference on Decision and Control (CDC), 2022
The linear quadratic regulator (LQR) problem is a cornerstone of control theory and a widely studied benchmark problem. When a system model is not available, the conventional approach to LQR design is indirect, i.e., based on a model identified from data.
Dorfler, F, Tesi, P, De Persis, C
openaire   +3 more sources

Direct Data Driven Control Using Noisy Measurements

CoRR
Submitted to IEEE ...
Ramin Esmzad, Gokul S. Sankar, Teawon Han, Hamidreza Modares   +3 more
openaire   +3 more sources

Adversarial Destabilization Attacks to Direct Data-Driven Control

CoRR
This study explores the vulnerability of direct data driven control, particularly in the linear quadratic regulator (LQR) problem, to adversarial perturbations in offline collected data. We focus on stealthy attacks that subtly alter training data to destabilize the closed-loop system while evading detection.
Hampei Sasahara
openaire   +3 more sources

Contextualizing the privacy paradox—a risk–benefit analysis of generation z’s adoption intentions toward AI-based virtual try-on [PDF]

Frontiers in Psychology
IntroductionWith the rapid advancement of artificial intelligence (AI), AI-driven virtual try-on (AI-VTO) services are reshaping consumption patterns in fashion retail.
Keren Mao, Rongrong Cui, Rongrong Cui, Zhicheng Wang, Zhicheng Wang   +4 more
doaj   +2 more sources

The neuron as a direct data-driven controller [PDF]

Proceedings of the National Academy of Sciences
In the quest to model neuronal function amid gaps in physiological data, a promising strategy is to develop a normative theory that interprets neuronal physiology as optimizing a computational objective. This study extends current normative models, which primarily optimize prediction, by conceptualizing neurons as optimal feedback controllers. We posit
Jason J. Moore, Alexander Genkin, Magnus Tournoy, Joshua L. Pughe-Sanford, Rob R. de Ruyter van Steveninck, Dmitri B. Chklovskii   +5 more
openaire   +4 more sources

Direct data-driven LPV control of nonlinear systems: An experimental result [PDF]

IFAC-PapersOnLine, 2023
We demonstrate that direct data-driven control of nonlinear systems can be successfully accomplished via a behavioral approach that builds on a Linear Parameter-Varying (LPV) system concept. An LPV data-driven representation is used as a surrogate LPV form of the data-driven representation of the original nonlinear system.
Verhoek, C., Abbas, H.S., Tóth, Roland
openaire   +4 more sources