Control of flexible-link manipulators using neural networks

✍ Scribed by H. A. Talebi PhD, R. V. Patel PhD, K. Khorasani PhD (auth.)

• Publisher: Springer-Verlag London
• Year: 2001
• Tongue: English
• Leaves: 155
• Series: Lecture Notes in Control and Information Sciences 261
• Edition: 1
• Category: Library

✦ Synopsis

Control of Flexible-link Manipulators Using Neural Networks addresses the difficulties that arise in controlling the end-point of a manipulator that has a significant amount of structural flexibility in its links. The non-minimum phase characteristic, coupling effects, nonlinearities, parameter variations and unmodeled dynamics in such a manipulator all contribute to these difficulties. Control strategies that ignore these uncertainties and nonlinearities generally fail to provide satisfactory closed-loop performance. This monograph develops and experimentally evaluates several intelligent (neural network based) control techniques to address the problem of controlling the end-point of flexible-link manipulators in the presence of all the aforementioned difficulties. To highlight the main issues, a very flexible-link manipulator whose hub exhibits a considerable amount of friction is considered for the experimental work. Four different neural network schemes are proposed and implemented on the experimental test-bed. The neural networks are trained and employed as online controllers.

✦ Table of Contents

Introduction....Pages 1-14
Manipulator model....Pages 15-32
Output redefinition....Pages 33-40
Proposed neural network structures....Pages 41-79
Experimental results....Pages 81-114

✦ Subjects

Control Engineering