Results 61 to 70 of about 9,285,453 (352)
Toward Mechanical Intelligence in Robotics
Robots can use their physical bodies to perform functions usually assigned to electronic sensors and controllers. This perspective defines mechanical intelligence through three core operations: filtering inputs, routing mechanical signals, and switching between states.
Xinyi Yang +5 more
wiley +1 more source
This paper deals with the model reference tracking control problem of linear systems based on the observer for Markov jump systems with unknown transition rates.
Weiqiang Song, Aijuan Jin
doaj +1 more source
Distributed Micropneumatic Sensors for Soft Robots to Detect Touch and Pose
Soft robots need integrated touch and pose sensing for safe and reliable operation. This work presents a three‐fingered soft gripper with 18 micropneumatic sensors made from the same materials as its pneumatic actuators. By measuring airflow resistance changes in deforming microchannels of the sensors, finger pose and contact are detected, enabling ...
Vilma Lampinen +3 more
wiley +1 more source
Modeling and feedforward compensation of air mounts with internal Helmholtz resonances
This paper presents a disturbance feedforward control strategy for active vibration isolation systems with internal air mount dynamics. First, a parametric model of an air mount system including a Helmholtz resonance is derived, which is an extension to ...
Butler, H. +3 more
core +1 more source
Ferroelectric Devices for In‐Memory and In‐Sensor Computing
Inspired by biological systems, in‐memory and in‐sensor computing overcome von Neumann bottlenecks. Ferroelectric devices can mimic synaptic functions and sense stimuli like light or force, therefore are ideal for these paradigms. This review introduces the ferroelectric devices applied for in‐memory and in‐sensor computing, covering their structures ...
Hong Fang +5 more
wiley +1 more source
Phase correction for learning feedforward control [PDF]
Intelligent mechatronics makes it possible to compensate for effects that are difficult to compensate for by construction or by linear control, by including some intelligence into the system. The compensation of state dependent effects, e.g. friction, cogging and mass deviation, can be realised by learning feedforward control.
de Kruif, Bas J., de Vries, Theo J.A.
openaire +1 more source
A machine learning‐assisted framework optimizes the KCl‐CaCl2‐LiCl ternary electrolyte. The optimized 13:35:52 mol% composition enables Ca‐based liquid metal batteries to operate stably at 480 °C, with >99.5% coulombic efficiency, ultralow self‐discharge, and excellent cycling stability, advancing low‐temperature large‐scale energy storage.
Xinglin Zhou +3 more
wiley +1 more source
Under the background of high permeability, voltage feedforward control may further weaken the stability of grid-connected inverter (GCI) systems and may cause sub-synchronous oscillation in extreme cases.
Weichen Qian, Jun Yin, Ziang Chen
doaj +1 more source
A pneumatically actuated multi‐tissue microphysiological system is integrated with AI‐based machine vision and automatic sampling and replenishment systems. The platform allows for the emulation of translationally relevant long‐term pharmacokinetic exposure scenarios for multiple weeks while enabling longitudinal monitoring of response biomarkers ...
Jibbe Keulen +15 more
wiley +1 more source
Adaptive feedforward control design for gust loads alleviation and LCO suppression
An adaptive feedforward controller is designed for gust loads alleviation and limit cycle oscillations suppression. Two sets of basis functions, based on the finite impulse response and modified finite impulse response approaches, are investigated to ...
Wang, Yongzhi +6 more
core +1 more source

