Results 101 to 110 of about 188,249 (289)
A stochastic optimal feedforward and feedback control methodology for superagility [PDF]
A new control design methodology is developed: Stochastic Optimal Feedforward and Feedback Technology (SOFFT). Traditional design techniques optimize a single cost function (which expresses the design objectives) to obtain both the feedforward and ...
Direskeneli, Haldun +2 more
core +1 more source
Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.In this research, a paradigm of parameter estimation method for pneumatic soft hand control is proposed. The method includes the following: 1) sampling harmonic damping waves, 2) applying pseudo‐rigid body modeling and the logarithmic decrement method, and 3) deriving position and force control.
Haiyun Zhang +4 more
wiley +1 more source
Machine Learning‐Driven Variability Analysis of Process Parameters for Semiconductor Manufacturing
Advanced Intelligent Systems, EarlyView.This research presents a machine learning approach that integrates nonlinear variation decomposition (NLVD) with statistical techniques to quantify the contribution of individual unit processes to performance and variance of figure of merit (FoM) at the LOT level.
Sinyeong Kang +6 more
wiley +1 more source
Feedforward equilibrium trajectory optimization with GSPulse
Nuclear FusionOne of the common tasks required for designing new plasma scenarios or evaluating capabilities of a tokamak is to design the desired equilibria using a Grad-Shafranov (GS) equilibrium solver.
J.T. Wai +7 more
doaj +1 more source
EMG‐Driven Telemetry and Inference System for Fish: Pose Reconstruction and Flow Sensing
Advanced Intelligent Systems, EarlyView.This work introduces an electromyography (EMG)‐driven telemetry framework that reconstructs body pose and infers hydrodynamic conditions in freely swimming fish. A custom 16‐channel archival system records intramuscular EMG, enabling deep‐learning models to decode joint kinematics, classify flow regimes, and reveal channel‐efficient sensing strategies.
Rahdar Hussain Afridi +7 more
wiley +1 more source
Data‐Driven Modeling of Forces Exerted by Pneumatic Actuators for a Pediatric Exosuit
Advanced Intelligent Systems, EarlyView.This work presents the experimental analysis and data‐driven modeling of the interaction forces between soft pneumatic actuators designed to assist upper‐extremity motion in a pediatric exosuit and an engineered test rig, across different experimental conditions: (A) force profiling of shoulder actuators, with varying actuator anchoring points and ...
Mehrnoosh Ayazi +4 more
wiley +1 more source
Enabling Stochastic Dynamic Games for Robotic Swarms
Advanced Intelligent Systems, EarlyView.This paper scales stochastic dynamic games to large swarms of robots through selective agent modeling and variable partial belief space planning. We formulate these games using a belief space variant of iterative Linear Quadratic Gaussian (iLQG). We scale to teams of 50 agents through selective modeling based on the estimated influence of agents ...
Kamran Vakil, Alyssa Pierson
wiley +1 more source
Application of a novel numerical simulation to biochemical reaction systems
Frontiers in Cell and Developmental BiologyRecent advancements in omics and single-cell analysis highlight the necessity of numerical methods for managing the complexity of biological data. This paper introduces a simulation program for biochemical reaction systems based on the natural number ...
Takashi Sato
doaj +1 more source
Advanced Intelligent Systems, EarlyView.This review explores the transformative impact of artificial intelligence on multiscale modeling in materials research. It highlights advancements such as machine learning force fields and graph neural networks, which enhance predictive capabilities while reducing computational costs in various applications.
Artem Maevskiy +2 more
wiley +1 more source
Advanced Intelligent Systems, EarlyView.Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal +6 more
wiley +1 more source