Adaptive smart card-based pull control systems in context-aware manufacturing systems: Training a neural network through multi-objective simulation optimization

2019 ◽  
Vol 75 ◽  
pp. 46-57
Author(s):  
Nesrine Azouz ◽  
Henri Pierreval
Keyword(s):  
Neural Network ◽  
Control Systems ◽  
Smart Card ◽  
Manufacturing Systems ◽  
Simulation Optimization ◽  
Context Aware ◽  
Multi Objective ◽  
Pull Control

A Discriminative Convolutional Neural Network with Context-aware Attention

2020 ◽  
Vol 11 (5) ◽  
pp. 1-21
Author(s):  
Yuxiang Zhou ◽  
Lejian Liao ◽  
Yang Gao ◽  
Heyan Huang ◽  
Xiaochi Wei
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Context Aware

scholarly journals Improvement of Heavy Load Robot Positioning Accuracy by Combining a Model-Based Identification for Geometric Parameters and an Optimized Neural Network for the Compensation of Nongeometric Errors

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Yuxiang Wang ◽  
Zhangwei Chen ◽  
Hongfei Zu ◽  
Xiang Zhang ◽  
Chentao Mao ◽  
...  
Keyword(s):  
Neural Network ◽  
Manufacturing Systems ◽  
Robot Manipulator ◽  
Joint Stiffness ◽  
Calibration Method ◽  
Geometric Parameters ◽  
Heavy Load ◽  
Positioning Accuracy ◽  
Robot Positioning ◽  
Residual Errors

The positioning accuracy of a robot is of great significance in advanced robotic manufacturing systems. This paper proposes a novel calibration method for improving robot positioning accuracy. First of all, geometric parameters are identified on the basis of the product of exponentials (POE) formula. The errors of the reduction ratio and the coupling ratio are identified at the same time. Then, joint stiffness identification is carried out by adding a load to the end-effector. Finally, residual errors caused by nongeometric parameters are compensated by a multilayer perceptron neural network (MLPNN) based on beetle swarm optimization algorithm. The calibration is implemented on a SIASUN SR210D robot manipulator. Results show that the proposed method possesses better performance in terms of faster convergence and higher precision.

Inverse Artificial Neural Network for Multi-Objective Antenna Design

2021 ◽  
pp. 1-1
Author(s):  
Li-Ye Xiao ◽  
Wei Shao ◽  
Fu-Long Jin ◽  
Bing-Zhong Wang ◽  
Qing Huo Liu
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Antenna Design ◽  
Multi Objective ◽  
Artificial Neural

Calculation of Bounding Sets for Neural Network Based Adaptive Control Systems

2008 ◽  
Author(s):  
Giampiero Campa ◽  
Marco Mammarella ◽  
Bojan Cukic ◽  
Yu Gu ◽  
Marcello Napolitano ◽  
...  
Keyword(s):  
Neural Network ◽  
Adaptive Control ◽  
Control Systems ◽  
Adaptive Control Systems
Sign in / Sign up

Export Citation Format

Share Document