Robot Control using an Artificial Neural Network: An Individual Undergraduate Project Report - Tapa blanda

Wandel, Olaf

 
9783838641416: Robot Control using an Artificial Neural Network: An Individual Undergraduate Project Report
Tapa blanda
ISBN 10: 3838641418 ISBN 13: 9783838641416
Editorial: Diplomarbeiten Agentur diplom.de, 1997

Sinopsis

Diplomarbeit, die am 31.05.1997 erfolgreich an einer Fachhochschule in Deutschland im Fachbereich Allgemeiner Maschinenbau eingereicht wurde. Abstract: The aim of the project was to control three joints of an industrial robot in terms of its position, velocity and acceleration. The work considered the necessary hardware, principles of neural networks and controlling techniques. The hardware comprised of a robot with three DC-motors and three optical position encoders, a personal computer with a D/A card for voltage output to the robot and two D/D cards. One D/D card for receiving values from the optical encoders and one for timing. The basics of artificial neural network type perceptrons were described. The special features bias, output feedback, momentum term, adjustment of momentum factor and adjustment of learning rate for this artificial neural network type were considered. An introduction to learning and control structures using artificial neural networks were given. These were controller copying, direct modelling, direct inverse modelling, control with a model and an inverse model, forward and inverse modelling, control action feedback error learning, feedback error learning, learning and control using the plant's Jacobian. The conversion of two learning and control structures, direct inverse modelling and control action feedback error learning, was implemented in software using "MS QuickBASIC 4.5". One joint was controlled with a direct inverse model. One joint and all joints together were controlled with control action feedback error learning. The results of experiments with these learning and control structures were documented. Table of Contents: 1.|Introduction|8 2.|The hardware|9 2.1|The robot|9 2.2|The computer and the software|11 2.3|The PCL-726 D/A card|11 2.4|The D/D card|11 2.5|The PCL-812 D/D card|12 2.6|The G64 rack|12 3.|Neural networks|13 3.1|The neuron|13 3.2|Conversion of neural networks|14 3.3|Learning

"Sinopsis" puede pertenecer a otra edición de este libro.

Reseña del editor

Inhaltsangabe:Abstract: The aim of the project was to control three joints of an industrial robot in terms of its position, velocity and acceleration. The work considered the necessary hardware, principles of neural networks and controlling techniques. The hardware comprised of a robot with three DC-motors and three optical position encoders, a personal computer with a D/A card for voltage output to the robot and two D/D cards. One D/D card for receiving values from the optical encoders and one for timing. The basics of artificial neural network type perceptrons were described. The special features bias, output feedback, momentum term, adjustment of momentum factor and adjustment of learning rate for this artificial neural network type were considered. An introduction to learning and control structures using artificial neural networks were given. These were controller copying, direct modelling, direct inverse modelling, control with a model and an inverse model, forward and inverse modelling, control action feedback error learning, feedback error learning, learning and control using the plant’s Jacobian. The conversion of two learning and control structures, direct inverse modelling and control action feedback error learning, was implemented in software using „MS QuickBASIC 4.5“. One joint was controlled with a direct inverse model. One joint and all joints together were controlled with control action feedback error learning. The results of experiments with these learning and control structures were documented. Inhaltsverzeichnis:Table of Contents: 1.Introduction8 2.The hardware9 2.1The robot9 2.2The computer and the software11 2.3The PCL-726 D/A card11 2.4The D/D card11 2.5The PCL-812 D/D card12 2.6The G64 rack12 3.Neural networks13 3.1The neuron13 3.2Conversion of neural networks14 3.3Learning principles of neural networks17 3.4Special modifications to the neural network used19 3.5Learning capacity22 4.Teaching and control techniques23 5.

Reseña del editor

Diploma Thesis from the year 1997 in the subject Engineering - Mechanical Engineering, grade: 1,0, Hamburg University of Applied Sciences (Allgemeiner Maschinenbau), language: English, abstract: Inhaltsangabe:Abstract: The aim of the project was to control three joints of an industrial robot in terms of its position, velocity and acceleration. The work considered the necessary hardware, principles of neural networks and controlling techniques. The hardware comprised of a robot with three DC-motors and three optical position encoders, a personal computer with a D/A card for voltage output to the robot and two D/D cards. One D/D card for receiving values from the optical encoders and one for timing. The basics of artificial neural network type perceptrons were described. The special features bias, output feedback, momentum term, adjustment of momentum factor and adjustment of learning rate for this artificial neural network type were considered. An introduction to learning and control structures using artificial neural networks were given. These were controller copying, direct modelling, direct inverse modelling, control with a model and an inverse model, forward and inverse modelling, control action feedback error learning, feedback error learning, learning and control using the plant s Jacobian. The conversion of two learning and control structures, direct inverse modelling and control action feedback error learning, was implemented in software using MS QuickBASIC 4.5 . One joint was controlled with a direct inverse model. One joint and all joints together were controlled with control action feedback error learning. The results of experiments with these learning and control structures were documented. Inhaltsverzeichnis:Table of Contents: 1.Introduction8 2.The hardware9 2.1The robot9 2.2The computer and the software11 2.3The PCL-726 D/A card11 2.4The D/D card11 2.5The PCL-812 D/D card12 2.6The G64 rack12 3.Neural networks13 3.1The neuron13 3.2Conversion of neural

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
Diplomarbeiten Agentur diplom.de
Año de publicación
1997
Idioma
Inglés
ISBN 10 
3838641418
ISBN 13 
9783838641416
Encuadernación
Tapa blanda
Número de páginas
54
Contacto del fabricante
kontakt@bedey-media.de
kontakt@bedey-media.de

Bramfelder Straße 102A
Hamburg
22305
Alemania