Application of neural networks to the flexible pole-cart balancing problem

Author

Dadios, Elmer P. ; Williams, David J.

Author_Institution

Dept. of Manuf. Eng., Loughborough Univ. of Technol., UK

Volume

3

fYear

1995

fDate

22-25 Oct 1995

Firstpage

2506

Abstract

This paper investigates the use of neural networks in the control of highly nonlinear systems. Online and off line control of a cart balancing a flexible pole under its first mode of vibration using neural networks is presented. Backpropagation and Kohonen´s self-organizing map have been used as neural network examples. The networks learned from a set of training data derived from a real system and were initially tested against a computer simulation of the derived dynamics of the flexible pole-cart balancing system and then applied to the real system

Keywords

backpropagation; flexible structures; neurocontrollers; nonlinear control systems; self-organising feature maps; Kohonen´s self organizing map; backpropagation; dynamics; flexible pole-cart balancing problem; highly nonlinear systems; neural networks; off line control; online control; vibration; Backpropagation; Biological neural networks; Biology computing; Computer networks; Computer simulation; Flexible manufacturing systems; Neural networks; Organizing; System testing; Training data;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man and Cybernetics, 1995. Intelligent Systems for the 21st Century., IEEE International Conference on

Conference_Location

Vancouver, BC

Print_ISBN

0-7803-2559-1

Type

conf

DOI

10.1109/ICSMC.1995.538158

Filename

538158