Results 131 to 140 of about 816,103 (361)

Artificial Intelligence‐Assisted Workflow for Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling

Advanced Materials, EarlyView.
AI‐Assisted Workflow for (Scanning) Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling. Abstract (Scanning) transmission electron microscopy ((S)TEM) has significantly advanced materials science but faces challenges in correlating precise atomic structure information with the functional properties of ...
Marc Botifoll, Ivan Pinto‐Huguet, Enzo Rotunno, Thomas Galvani, Catalina Coll, Payam Habibzadeh Kavkani, Maria Chiara Spadaro, Yann‐Michel Niquet, Martin Børstad Eriksen, Sara Martí‐Sánchez, Georgios Katsaros, Giordano Scappucci, Peter Krogstrup, Giovanni Isella, Andreu Cabot, Gonzalo Merino, Pablo Ordejón, Stephan Roche, Vincenzo Grillo, Jordi Arbiol   +19 more
wiley   +1 more source

A novel adaptive PD-type iterative learning control of the PMSM servo system with the friction uncertainty in low speeds. [PDF]

PLoS One, 2023
Riaz S, Qi R, Tutsoy O, Iqbal J.
europepmc   +1 more source

Set-to-set iterative learning control

Automatica
This work introduces a novel set-to-set (STS) iterative learning control (ILC) framework which generalizes the ideas of point-to-point ILC (PTP ILC) and region-to-region (RTR ILC) techniques. The existing ILC frameworks are extended by tracking both sets and points at desired times within an iteration.
Reid D. Smith, Andrew G. Alleyne
openaire   +2 more sources

Beyond Presumptions: Toward Mechanistic Clarity in Metal‐Free Carbon Catalysts for Electrochemical H2O2 Production via Data Science

Advanced Materials, EarlyView.
Metal‐free carbon catalysts enable the sustainable synthesis of hydrogen peroxide via two‐electron oxygen reduction; however, active site complexity continues to hinder reliable interpretation. This review critiques correlation‐based approaches and highlights the importance of orthogonal experimental designs, standardized catalyst passports ...
Dayu Zhu, Hsi‐wen Wu, Xiao Wang, Jie Zhang   +3 more
wiley   +1 more source

Model-based decoupling control method for dual-drive gantry stages : A case study with experimental validations

, 2013
La version éditeur de cet article est disponible à l'adresse suivante : http://dx.doi.org/10.1016/j.conengprac.2012.10.010Industrial motion control of dual–drive gantry stages is usually performed by position controllers acting independently on each ...
COLEMAN, Ralph, GOMAND, Julien, KESTELYN, Xavier, BARRE, Pierre-Jean, GARCÍA-HERREROS, Iván   +4 more
core   +1 more source

Bridging Reinforcement Learning and Iterative Learning Control: Autonomous Motion Learning for Unknown, Nonlinear Dynamics. [PDF]

Front Robot AI, 2022
Meindl M, Lehmann D, Seel T.
europepmc   +1 more source

Intelligent Acousto‐Electrical Metamaterials (IAM) for Sound Source Detection

Advanced Materials, EarlyView.
Our proposed metamaterial concept enables sound source detection using a single material, in contrast to conventional arrays that require dozens or even hundreds of transducers. We show that the coupled acoustic–vibrational–electrical responses in piezoelectric metamaterials give rise to topology‐governed charge transport, producing distinct voltage ...
Victor Couëdel, Haotian Lu, Jiayan Zhang, Desheng Yao, Ananya Bhardwaj, Ramiro Contreras, Karim Sabra, Xiaoyu (Rayne) Zheng   +7 more
wiley   +1 more source

LMI based stability analysis and robust controller design for discrete linear repetitive processes

, 2003
Discrete linear repetitive processes are a distinct class of 2D linear systems with applications in areas ranging from long-wall coal cutting through to iterative learning control schemes.
Owens, D H, Rogers, E, Paszke, W, Lam, J, Owens, DH, Galkowski, K, Sulikowski, B, Xu, S   +7 more
core   +1 more source

Iterative Dissipativity of Partial Difference Equation Dynamics in Open-Loop Iterative Learning Control Mode

Mathematics
Complex physical processes, which could evolve in both spatial and temporal dimensions and be represented by partial difference equations, could also operate in a repetitive mode with iterative learning methods as suitable control laws.
Tengfei Xiao
doaj   +1 more source

Batch-to-Batch Adaptive Iterative Learning Control-Explicit Model Predictive Control Two-Tier Framework for the Control of Batch Transesterification Process. [PDF]

ACS Omega, 2022
Gupta N, De R, Kodamana H, Bhartiya S.
europepmc   +1 more source