Intelligent Synchronous Control for Gantry Position Stage

2014 ◽  
Vol 620 ◽  
pp. 317-320
Author(s):  
Po Huan Chou ◽  
Faa Jeng Lin ◽  
Wen Chuan Chen ◽  
Ying Min Chen
Keyword(s):  
External Disturbance ◽  
Back Propagation ◽  
Field Oriented Control ◽  
Servo Drive ◽  
Control Approach ◽  
Synchronous Control ◽  
Linear Motors ◽  
On Line ◽  
On Line Learning ◽  
Servo Drive System

A cross-coupled proportional-integral-derivative neural network (PIDNN) control is proposed in this study for the synchronous control of a dual linear motors servo system which is installed in a gantry position stage. First, the dynamics of the field-oriented control PMLSM servo drive with a lumped uncertainty, which contains parameter variations, external disturbance and friction force, is introduced. Then, to achieve accurate trajectory tracking performance with robustness, an intelligent control approach using PIDNN is proposed for the field-oriented control PMLSM servo drive system. In the proposed approach, the on-line learning algorithms of the PIDNN are derived using back-propagation (BP) method to guarantee the convergence of the network. Finally, some experimental results are illustrated to depict the validity of the proposed control approach.

scholarly journals On-line learning with adaptive back-propagation in two-layer networks

1997 ◽  
Vol 56 (3) ◽  
pp. 3426-3445 ◽  
Author(s):  
Ansgar H. L. West ◽  
David Saad
Keyword(s):  
Back Propagation ◽  
On Line ◽  
On Line Learning

scholarly journals Mood-Based on-Line Learning System

2019 ◽  
Vol 8 (6S3) ◽  
pp. 2141-2145
Keyword(s):  
Genetic Algorithm ◽  
Online Learning ◽  
Learning Environments ◽  
Facial Expressions ◽  
Back Propagation ◽  
Learning System ◽  
Online Learning Environments ◽  
Face Images ◽  
On Line ◽  
On Line Learning

Many millennial learners are associated with massive open on-line courses for learning. This online learning to be more interactive and to substitute the teacher observation, it requires the augmentation of those humanly traits, to keep the learner active. This paper proposes such a sub-system to the online learning environments which performs necessary activities to bring the learner into pace of the course. From the reactions of learner while learning from the continuous capturing of face images, this system can analyze the emotions and initiate the necessary actions to continue the learning. The Emotional Back Propagation Neural Networks with successful PCA were used for training and Genetic Algorithm is used for optimizing the results. The system can automatically identify the facial expressions and initiates the counter actions to keep the learning successful.

Patterns of Implicit Learning Below the Level of Conscious Knowledge

2010 ◽  
Vol 24 (2) ◽  
pp. 91-101 ◽  
Author(s):  
Juliana Yordanova ◽  
Rolf Verleger ◽  
Ullrich Wagner ◽  
Vasil Kolev
Keyword(s):  
Implicit Learning ◽  
Explicit Knowledge ◽  
Implicit Knowledge ◽  
Knowledge Generation ◽  
Sleep Stages ◽  
Implicit Processing ◽  
Implicit Processes ◽  
Late Night ◽  
On Line ◽  
On Line Learning

The objective of the present study was to evaluate patterns of implicit processing in a task where the acquisition of explicit and implicit knowledge occurs simultaneously. The number reduction task (NRT) was used as having two levels of organization, overt and covert, where the covert level of processing is associated with implicit associative and implicit procedural learning. One aim was to compare these two types of implicit processes in the NRT when sleep was or was not introduced between initial formation of task representations and subsequent NRT processing. To assess the effects of different sleep stages, two sleep groups (early- and late-night groups) were used where initial training of the task was separated from subsequent retest by 3 h full of predominantly slow wave sleep (SWS) or rapid eye movement (REM) sleep. In two no-sleep groups, no interval was introduced between initial and subsequent NRT performance. A second aim was to evaluate the interaction between procedural and associative implicit learning in the NRT. Implicit associative learning was measured by the difference between the speed of responses that could or could not be predicted by the covert abstract regularity of the task. Implicit procedural on-line learning was measured by the practice-based increased speed of performance with time on task. Major results indicated that late-night sleep produced a substantial facilitation of implicit associations without modifying individual ability for explicit knowledge generation or for procedural on-line learning. This was evidenced by the higher rate of subjects who gained implicit knowledge of abstract task structure in the late-night group relative to the early-night and no-sleep groups. Independently of sleep, gain of implicit associative knowledge was accompanied by a relative slowing of responses to unpredictable items suggesting reciprocal interactions between associative and motor procedural processes within the implicit system. These observations provide evidence for the separability and interactions of different patterns of processing within implicit memory.

SCROLLA — On-Line Learning and Assessment

2001 ◽  
Vol 1 (2) ◽  
pp. 27-27
Author(s):  
Cliff Beevers
Keyword(s):  
On Line ◽  
On Line Learning
Sign in / Sign up

Export Citation Format

Share Document