On-line process optimization: parameter tuning for the real time evolution (RTE) approach

2004 ◽  
Vol 28 (5) ◽  
pp. 661-672 ◽  
Author(s):  
Sebastián Eloy Sequeira ◽  
Miguel Herrera ◽  
Moisès Graells ◽  
Luis Puigjaner
Keyword(s):  
Real Time ◽  
Time Evolution ◽  
Process Optimization ◽  
Parameter Tuning ◽  
The Real ◽  
Optimization Parameter ◽  
On Line ◽  
Line Process

The Real-Time Prediction of Surface Roughness Based on Genetic Wavelet Network

2010 ◽  
Vol 102-104 ◽  
pp. 610-614 ◽  
Author(s):  
Jun Chi ◽  
Lian Qing Chen
Keyword(s):  
Surface Roughness ◽  
Real Time ◽  
Back Propagation ◽  
Cutting Parameters ◽  
Wavelet Network ◽  
Back Propagation Algorithm ◽  
The Real ◽  
Roughness Model ◽  
On Line ◽  
Artificial Network

A methodology based on relax-type wavelet network was proposed for predicting surface roughness. After the influencing factors of roughness model were analyzed and the modified wavelet pack algorithm for signal filtering was discussed, the structure of artificial network for prediction was developed. The real-time forecast on line was achieved by the nonlinear mapping and learning mechanism in Elman algorithm based on the vibration acceleration and cutting parameters. The weights in network were optimized using genetic algorithm before back-propagation algorithm to reduce learning time.The validation of this methodology is carried out for turning aluminum and steel in the experiments and its prediction error is measured less than 3%.

On-Line Process Optimization in a North Sea Field

1997 ◽  
Author(s):  
Y. Jalali ◽  
W. Van Wassenhove ◽  
C. Romano ◽  
R. Pickles
Keyword(s):  
Process Optimization ◽  
North Sea ◽  
On Line ◽  
Line Process

Simulated On-Line Process Optimization of a Robotic Materials Handling System

1986 ◽  
Vol 108 (3) ◽  
pp. 285-291
Author(s):  
M. S. King ◽  
J. K. Blundell
Keyword(s):  
Process Optimization ◽  
Kinematic Model ◽  
Industrial Robots ◽  
Time Varying ◽  
Optimization Strategy ◽  
Materials Handling ◽  
On Line ◽  
Line Process ◽  
Time Varying Environment ◽  
Varying Environment

Industrial robots in use today lack the total ability to perceive and interact with their environment. This limitation is a major obstacle confronting robotic systems developers. This work outlines an on-line process optimization strategy which allows a robot to work within a time-varying environment. After developing the kinematic model of the robot and its relationship to its environment, the process optimization strategy is simulated. The performance of the system is measured by using an index of performance and comparing the simulation results against a series of non-optimized models. The results indicate that on-line process optimization strategy significantly increases the performance of a robotic system operating in a time-varying environment.

scholarly journals The Real-Time Evolution of Sakurai's Star (V4334 Sgr) and other (V)LTP Objects

2006 ◽  
Vol 2 (S234) ◽  
pp. 75
Author(s):  
P.A.M. van Hoof ◽  
M. Bryce ◽  
A. Evans ◽  
S.P.S. Eyres ◽  
M. Hajduk ◽  
...  
Keyword(s):  
Real Time ◽  
Time Evolution ◽  
The Real
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