Instrumentacion

Solo disponible en BuenasTareas
  • Páginas : 116 (28786 palabras )
  • Descarga(s) : 0
  • Publicado : 2 de marzo de 2011
Leer documento completo
Vista previa del texto
ADVANCED CONTROL OF A ROTARY DRYER

L EENA YLI NIEMI
Department of Process Engineering

O UL U 1 9 9 9

LEENA YLINIEMI

ADVANCED CONTROL OF A ROTARY DRYER

Academic Dissertation to be presented with the assent of the Faculty of Technology, University of Oulu, for public discussion in Raahensali (Auditorium L 10), Linnanmaa, on June 29th, 1999, at 12 noon.

O U LU N Y LI O P IS T O, O U LU 1 99 9

Copyright © 1999 Oulu University Library, 1999

Manuscript received 31.5.1999 Accepted 1.6.1999

Communicated by Associate Professor António Dourado Correia Professor Sirkka-Liisa Jämsä-Jounela

ISBN 951-42-5281-0 (URL: http://herkules.oulu.fi/isbn9514252810/) ALSO AVAILABLE IN PRINTED FORMAT ISBN 951-42-5280-2 ISSN 0355-3213

(URL:http://herkules.oulu.fi/issn03553213/)

OULU UNIVERSITY LIBRARY OULU 1999

Dedicated to Ilkka, Mari and Anna

Real knowledge is based on experience. (Chinese saying)

Yliniemi, Leena, Advanced control of a rotary dryer Department of Process Engineering, University of Oulu, FIN-90570 Oulu 1999 Oulu, Finland (Manuscript received 31 May, 1999)

Abstract Drying, especially rotary drying, is without doubt one of the oldestand most common unit operations in the process industries. Rotary dryers are workhorses which are easy and reliable to operate, but neither energy-efficient nor environmentally friendly. In order to conform better to the requirements of modern society concerning working conditions, safety practices and environmental aspects, the development of control systems can provide opportunities for improvingdryer operation and efficiency. Our in depth understanding of rotary drying is poor, because it is a very complex process that includes the movement of solids in addition to thermal drying. Thus even today rotary dryers are controlled partly manually, based on the operator’ ”eye” and s experience, and partly relying on conventional control methods. The control of a rotary dryer is difficult due tothe long time delay, which means that accidental variations in the input variables can disturb the process for long periods of time before they are reflected in the output variables. To eliminate such disturbances at an early stage, increasing interest has been shown in more sophisticated control systems such as model-based constructs, fuzzy logic and neural nets in recent years. Although it hasproved difficult and time-consuming to develop model-based control systems, due to the complexity of the process, intelligent control methods based on fuzzy logic and neural nets offer attractive solutions for improving dryer control. These methods make it possible to utilise experience, knowledge and historical data, large amounts of which are readily available. The aim of this research was toimprove dryer control by developing new hybrid control systems, one consisting of a fuzzy logic controller (FLC) and PI controller and the other of a three-layer neural network (NN) and PI controller. The FLC and NN act as supervisory controllers giving set points for the PI controllers. The performance of each was examined both with simulations and in pilot plant experiments. The pilot plant dryerat the University of Oulu closely resembles a real industrial situation, so that the results are relevant. Evaluation of these results showed that the intelligent hybrid controllers are well suited for the control of a rotary dryer, giving a performance in which disturbances can be eliminated rapidly and operation of the dryer can thereby be improved, with the aim of enhancing its efficiency andenvironmental friendliness.

Keywords:

rotary drying, fuzzy logic, neural networks, hybrid control

Acknowledgements
This thesis is based on work carried out in the Control Engineering Laboratory, Department of Process Engineering, University of Oulu. Research into the modelling and control of a rotary dryer was started in the early 1980’ as a three-year industrial project s supervised...
tracking img