Results 111 to 120 of about 9,285,453 (352)
Data‐Efficient Cycle‐Level Capacity Prediction Using 1D Deep Convolutional Network
We introduce DeepBat, a deep learning framework featuring a 1D convolutional backbone designed to extract latent degradation patterns from a microstructurally diverse electrode dataset. By learning complex formulation–performance relationships, the model accurately predicts long‐term specific discharge capacity using limited early‐cycle data, providing
Tao Huang +16 more
wiley +1 more source
This paper investigates a novel adaptive voltage control over a three-phase grid-forming (GFM) inverter. The proposed voltage controller includes two function parts: power control input and signal control input. The former improves dynamic performance by
Renzhi Huang +6 more
doaj +1 more source
ABSTRAK Sebuah konverter daya multilevel inverter diharapkan mampu untuk menyuplai tegangan AC ideal pada kondisi beban linier maupun nonlinier. Diharapkan metode kendali mampu cepat tanggap dan mampu mempertahankan bentuk tegangan AC keluaran inverter.
MOCHAMAD ARI BAGUS NUGROHO +2 more
doaj +1 more source
Design and performance tradeoffs in MIMO disturbance feedforward control
Disturbance feedforward control (DFC) can be used to reject external disturbances that are a priori unknown. This paper addresses the design and performance tradeoffs due to the causal nature of DFC in Multi-Input Multi-Output (MIMO) systems. Performance
Cong, Bo +2 more
core +1 more source
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
RNA editing: new roles in feedback and feedforward control. [PDF]
Fu XD.
europepmc +1 more source
Experiments of feedforward control on a conventional industrial manipulator
In this paper, feedforward model-based control is experimented on a conventional industrial manipulator, the SMART-3 6.12R by COMAU. Despite of the fact that the conditions for the experiments are far from those provided by research set-ups, the obtained
CHIACCHIO, Pasquale +3 more
core +1 more source
Ecoefficiency Analysis and Regression in Data Conversion for Spiking Neural Network Training
The environmental footprint of spiking neural networks is quantified during dataset encoding and training for autonomous driving regression across three benchmarks. Temporal depth emerges as the dominant driver of energy consumption and CO2 emissions, while the accuracy–energy trade‐off proves dataset‐dependent. On conventional hardware, spiking models
Fernando S. Martínez +3 more
wiley +1 more source
With the continuous progress of new energy technology, new energy vehicles have ushered in a stage of rapid development. As the central core of new energy vehicle, the power accumulator batteries have been attracting increasing attention.
Jingang Han +3 more
doaj +1 more source
In weak grid, feedforward of grid voltage control is widely used to effectively suppress grid-side current distortion of inverters caused by harmonics in point of common coupling (PCC) voltage. However, due to its introduction of a positive feedback loop
Su’e Wang, Kaiyuan Cui, Pengfei Hao
doaj +1 more source

