Results 61 to 70 of about 303,155 (330)
A survey of methods for handling initial state shifts in iterative learning control
Heliyon, 2023 This paper introduces three types of controllers: a PID-type iterative learning controller, an adaptive iterative learning controller, and an optimal iterative learning controller, and reviews the history and research status of initial shifts rectifying ...
Dongjie Chen, Tiantian Lu, Guojun Li
doaj +1 more source
Local Regularization Assisted Orthogonal Least Squares Regression
, 2006 A locally regularized orthogonal least squares (LROLS) algorithm is proposed for constructing parsimonious or sparse regression models that generalize well.
Chen, S.
core +1 more source
PASTA‐ELN: Simplifying Research Data Management for Experimental Materials Science
Advanced Engineering Materials, EarlyView.Research data management faces ongoing hurdles as many ELNs remain complex and restrictive. PASTA‐ELN offers an open‐source, cross‐platform solution that prioritizes simplicity, offline access, and user control. Its in tuitive folder structure, modular Python add‐ons, and open formats enable seamless documentation, FAIR data practices, and easy ...
S. Brinckmann, G. Winkens, R. Schwaiger
wiley +1 more source
A Topology Optimization Framework for the Inverse Design of Nonlinear Mechanical Metamaterials
Advanced Engineering Materials, EarlyView.This work uses topology optimization to design unit cells for mechanical metamaterials with a prescribed nonlinear stress–strain response. The framework adds contact and postbuckling modeling to synthesize microstructures for three highly nonlinear responses, including pseudoductile behavior, monostable with snap‐through buckling, and bistable ...
Charlie Aveline +2 more
wiley +1 more source
Advanced Functional Materials, EarlyView.The layer‐by‐layer (LbL) assembly of coordination solids, enabled by the surface‐mounted metal‐organic framework (SURMOF) platform, is on the cusp of generating the organic counterpart of the epitaxy of inorganics. The programmable and sequential SURMOF protocol, optimized by machine learning (ML), is suited for accessing high‐quality thin films of ...
Zhengtao Xu +2 more
wiley +1 more source
Learning-Gain-Adaptive Iterative Learning Control to Linear Discrete-Time-Invariant Systems
IEEE Access, 2019 For a class of repetitive linear discrete-time-invariant systems with the unit relative degree, a learning-gain-adaptive iterative learning control (LGAILC) mechanism is exploited, for which the iteration-wise performance index is to maximize the ...
Xiaohui Li, Xiaoe Ruan, Yan Liu
doaj +1 more source
Advanced Functional Materials, EarlyView.An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone +11 more
wiley +1 more source
Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
Advanced Functional Materials, EarlyView.A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore +7 more
wiley +1 more source
Iterative Learning Control Combination with Adaptive Sliding Mode Technique for a Hypersonic Vehicle
Xibei Gongye Daxue Xuebao, 2019 Aiming at the complicated nonlinearities, high uncertainties and strong coupling of hypersonic vehicle, a new adaptive iterative learning control method is put forward. The proposed controller combined iterative learning control with sliding mode control.
doaj +1 more source
Distributed Learning for Stochastic Generalized Nash Equilibrium Problems
, 2017 This work examines a stochastic formulation of the generalized Nash equilibrium problem (GNEP) where agents are subject to randomness in the environment of unknown statistical distribution.
Sayed, Ali H. +2 more
core +1 more source