Results 151 to 160 of about 816,103 (361)
A Regret Minimization Approach to Iterative Learning Control
, 2021 We consider the setting of iterative learning control, or model-based policy learning in the presence of uncertain, time-varying dynamics. In this setting, we propose a new performance metric, planning regret, which replaces the standard stochastic ...
Hazan, Elad +3 more
core
AI–Guided 4D Printing of Carnivorous Plants–Inspired Microneedles for Accelerated Wound Healing
Advanced Materials, EarlyView.This work presents an artificial intelligence (AI)‐guided 4D‐printed microneedle platform inspired by carnivorous plants for wound healing. A thermo‐responsive shape memory polymer enables body temperature–triggered self‐coiling for autonomous wound closure.
Hyun Lee +21 more
wiley +1 more source
Advanced Materials, EarlyView.This review summarizes the principles and challenges of nonaqueous lithium‐oxygen batteries and recent advances in cathode catalysts, including carbon‐based materials, metals, oxides, sulfides, nitrides, carbides, and redox mediators. It highlights emerging design strategies and artificial intelligence‐driven approaches, emphasizing data‐assisted ...
Yuqing Yao +8 more
wiley +1 more source
Advances in Magnesium‐Based Thermoelectrics: A Critical Review
Advanced Materials, EarlyView.Magnesium‐based thermoelectric materials have emerged as promising candidates for low‐to‐mid‐temperature energy conversion due to their abundance, low cost, and competitive performance. This review summarizes recent advances in Mg3X2, MgAgSb, and Mg2X systems, covering transport mechanisms, fabrication strategies, stability challenges, and device ...
Li‐Min Zhang +5 more
wiley +1 more source
Weaving Intelligence: Thermally Drawn Multimaterial Fibers Toward AI‐Enabled Smart Textiles
Advanced Materials, EarlyView.Thermally drawn multimaterial fibers are rapidly advancing as intelligent structural units for next‐generation smart textiles. Integrating multimaterial architectures with neuromorphic and spiking‐neural‐network principles enables fabrics that can sense, compute, and adapt autonomously.
Vuong Dinh Trung +9 more
wiley +1 more source
Advanced Materials, EarlyView.A deep learning inverse‐design framework is established to create versatile reconfigurable terahertz metadevices. By synergizing deep learning with phase‐change materials, this approach enables on‐demand customization of multidimensional electromagnetic responses.
Yisheng Dong +11 more
wiley +1 more source
Noncausal finite-time robust Iterative Learning Control
, 2007 In this paper, we present a new finite-time robust Iterative Learning Control (ILC) strategy which can guarantee robust stability of the ILC controlled system in presence of model uncertainty as quantified by an additive or multiplicative uncertainty ...
Bosgra, O.H. +3 more
core +1 more source
Jixie chuandong, 2011 The study on optimization design and iterative learning trajectory tracking control of hybrid-driven planar five-bar mechanism is carried out.Firstly,genetic algorithm is applied to optimization design of the hybrid-driven planar five-bar mechanism ...
曹建斌, 訾斌
doaj
Advanced Materials Technologies, EarlyView.This study explores how machine learning models, trained on small experimental datasets obtained via Phase Doppler Anemometry (PDA), can accurately predict droplet size (D32) in ultrasonic spray coating (USSC). By capturing the influence of ink complexity (solvent, polymer, nanoparticles), power, and flow rate, the model enables precise droplet control
Pieter Verding +5 more
wiley +1 more source
High-order open and closed loop iterative learning control scheme with initial state learning
, 2004 In this paper, a high order open and closed ILC (iterative learning control) scheme with initial state learning is presented. The convergent hounds are only dependent on the system uncertainties and disturbances but independent of the initialization ...
Tan DL(谈大龙) +3 more
core