Abstract
Drying, especially rotary drying, is without doubt one of
the oldest and 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
improving dryer 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's "eye" and
experience, and partly relying on conventional control methods.
The control of a rotary dryer is difficult due to the 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 has proved 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 utilize experience,
knowledge and historical data, large amounts of which are readily
available.
The aim of this research was to improve 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 dryer at 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 and environmental friendliness.
| Identifer | oai:union.ndltd.org:oulo.fi/oai:oulu.fi:isbn951-42-5281-0 |
| Date | 01 June 1999 |
| Creators | Yliniemi, L. (Leena) |
| Publisher | University of Oulu |
| Source Sets | University of Oulu |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/doctoralThesis, info:eu-repo/semantics/publishedVersion |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess, © University of Oulu, 1999 |
| Relation | info:eu-repo/semantics/altIdentifier/pissn/0355-3213, info:eu-repo/semantics/altIdentifier/eissn/1796-2226 |
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