Results 101 to 110 of about 9,285,453 (352)

Advances in Thermal Modeling and Simulation of Lithium‐Ion Batteries with Machine Learning Approaches

Advanced Intelligent Discovery, EarlyView.
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin, Kang Fu, Junjie Ding, Kai Sun, Peng Tan   +4 more
wiley   +1 more source

Tuning rules for feedforward control from measurable disturbances combined with PID control a review

Feedforward control can be considered as the most well-known control approach to deal with measurable disturbances. It started to be used almost 100 years ago, and since then it is being used in most industrial processes.
Hägglund, T.,, Guzmán, J. L.,, Lund University.   +2 more
core   +1 more source

Parametric Analysis of Spiking Neurons in 16 nm Fin Field‐Effect Transistor Technology

Advanced Intelligent Discovery, EarlyView.
Energy efficient computing has driven a shift toward brain‐inspired neuromorphic hardware. This study explores the design of three distinct silicon neuron topologies implemented in 16 nm fin field‐Effect transistor technology. While the Axon‐Hillock design achieves gigahertz throughput, its functional fragility persists. The Morris–Lecar model captures
Logan Larsh, Raiyan Siddique, Sarah S. Sharif, Yaser Mike Banad   +3 more
wiley   +1 more source

Control-Oriented Neural Network Quantization in Feedforward Control System

SICE Journal of Control, Measurement, and System Integration
In this paper, we focus on the weight quantization problem of neural networks, which is essential for practical implementation in control systems. In our previous work, we proposed a weight coefficient quantization method that preserves the intrinsic ...
Naoki Tsubone, Yuki Minami, Masato Ishikawa   +2 more
doaj   +1 more source

A Parallel GRU-Transformer Neural Network Approach for Feedforward Compensation in Precision Motion Platform Control

IEEE Access
This paper proposes a feedforward compensation strategy based on Parallel GRU-Transformer neural network to address the issues of large tracking errors and insufficient stability of multi degree of freedom precision motion platforms in complex dynamic ...
Yi-Min Wang, Jun-Jie Wang, Ji-Teng Yang, Bin Liu, Shi Bu, Xi Chen, Jian-Ping Xing   +6 more
doaj   +1 more source

Large‐Scale Machine Learning to Screen for Small‐Molecule Senolytics

Advanced Intelligent Discovery, EarlyView.
A consistent workflow underpins all experiments in this study. A dedicated model‐selection dataset first identifies optimal hyperparameters for each algorithm. Models are then trained and rigorously evaluated on independent sets of molecules using the senolytic ratio SR. Comprehensive hyperparameter exploration across SMILES representations, task types,
Alexis Dougha, Jesus Gil, Pedro J. Ballester   +2 more
wiley   +1 more source

The Control of Non Isothermal CSTR Using Different Controller Strategies

Iraqi Journal of Chemical and Petroleum Engineering, 2012
In all process industries, the process variables like flow, pressure, level, concentration and temperature are the main parameters that need to be controlled in both set point and load changes.
Zahra'a F. Zuhwar
doaj  

Research and Experiment on an Adaptive Feedforward Compensation Composite Control Strategy for an Electro-Hydraulic Servo System

IEEE Access
In order to reduce the tracking and response errors of the electro-hydraulic servo system, improve the dynamic response quality of the system, enhance the adaptive ability of the system, and effectively solve the common problems of nonlinear interference
Mei Luhai
doaj   +1 more source

Designing and tuning robust feedforward controllers

Computers & Chemical Engineering, 2004
Abstract A model-based design and tuning procedure is proposed for feedforward controllers, which accounts for model uncertainties in SISO systems. Proper relationships for the analysis of feedforward–feedback control systems show that tuning the feedforward controller is not completely independent from the feedback-loop spectral characteristics ...
Eduardo J. Adam, Jacinto L. Marchetti
openaire   +3 more sources

Feedforward Control in the Paper Machine Drying Section

, 2006
A new disturbance signal was introduced for the paper machine drying section and its feedforward control was evaluated. Control of the moisture content is conventionally accomplished by adjusting the steam pressure in the cylinders. By adding feedforward
Stenström, Stig,, Hägglund, Tore,, Lund University., Karlsson, Magnus,, Slätteke, Ola,   +4 more
core