Leena Yliniemi

Advanced Control of a Rotary Dryer

Abstract Two kinds of intelligent, hybrid control systems for a rotary dryer are presented. The main controlled variable is the output moisture of solids and the main manipulated variable is the input temperature of drying air which correlates to the fuel flow. The main disturbances of the process are the input moisture of solids and the feed flow. The one discussed control system includes a fuzzy logic controller (FLC) and a PI-controller and the other a neural network controller and a PI-controller. In both cases the intelligent controller determines the set point value to a PI controller. The control results have been examined both with simulations and with pilot plant experiments.

Data-driven fuzzy modelling of a rotary dryer

It was examined how different fuzzy modelling approaches, such as neuro-fuzzy, fuzzy clustering and linguistic equation methods, apply to the modelling of a rotary dryer. Because rotary drying, one of the oldest process in industry, is a highly nonlinear, strongly interactive multivariable process, its modelling is a demanding task. Its mathematical model, consisting of partial differential equations with several experimental parameters, is very complex and cumbersome. Therefore, the data-driven model is attractive, especially because many experimental observations and operating experience exist. The paper describes the fuzzy modelling approaches applied to the modelling of a rotary dryer. The applicability of different approaches has been evaluated by simulations, with the data collected from a pilot plant rotary dryer. The performance was estimated by an error index root means squared method and by comparing the modelling results with the results achieved by a linear regression model and a neural network model. The results show that neuro-fuzzy, fuzzy clustering and linguistic equation methods apply well, and no big differences can be detected between the methods.

Design of Adaptive Fuzzy Controllers

This chapter has introduced the design of adaptive fuzzy controllers. These controllers are used in direct control of process variables and in this way replacing conventional PI-controllers. Good results have been gained with rather simple structures that are also easy to install and maintain. However, their design includes quite many manual stages that require expert knowledge.

SELF-TUNING FUZZY CONTROL OF A ROTARY DRYER

Abstract Drying, especially rotary drying is without doubt one of the oldest and most common unit operations in industries. It is a very complex non-linear process including the movement of solids in addition to thermal drying. This means that both the modelling and control of a rotary dryer is difficult with conventional methods. The aim of this research was to improve dryer control by developing control systems based on self-tuning PID-type fuzzy logic controllers. The behaviour of the control systems has been tested with simulations based on the model of a pilot plant dryer located in the Control Engineering Laboratory at the University of Oulu. The control results have been compared achieved with a conventional PID controller.

Using WWW To Support Control Engineering Training

Abstract The fast development in the field of process automation together with the reduction in teaching resources, and in increasing number of students forces educational establishments to consider new and more effective learning methods. The recent development in the fields of hypermedia, computer, and network technology makes it possible to utilise computer and network based learning to meet these new demands. Since 1997 Control Engineering Laboratory at the University of Oulu has used a web server as an information channel to support teaching. The web utilises the basic web technology, although the integration with new learning environment programs is under consideration. At the moment, Control Engineering Laboratory, is building a learning environment on the basic web environment. Into this environment, such components that will extend the basic concept of the learning environment are included. In this paper, the web, some parts of its contents, and usage are described.

Adaptive Fuzzy Control of a Rotary Dryer

Drying, especially rotary drying is without doubt one of the oldest and most usual unit operations in process industries. Rotary dryers are workhorses, the operation of which is easy and sure, but neither energy efficient nor environmentally friendly. To answer better to the requirements of the modern society concerning working conditions, safety practices and environmental aspects the sophisticated control offers the opportunity to improve dryer operation and efficiency.

Fuzzy modelling of a rotary dryer

Abstract In this paper a fuzzy model for a rotary dryer has been developed using different fuzzy modelling methods as neuro fuzzy, fuzzy clustering and linguistic equations methods. The performance of the fuzzy model applied to a pilot plant rotary dryer has been estimated by comparing the output of the fuzzy model i.e. the output moisture of solids with the moisture measurements collected from the pilot dryer for training and testing purposes of the model. Also the comparison between the fuzzy model and the linear regression model or neural network model of the dryer is made.

Intelligent Methods in the Electric Arc Furnace Control

Abstract The aim of the research described in this paper is to improve the control of the electric arc furnace (EAF) by using intelligent control methods. The operation of impedance control was analysed with the help of data acquisition and the first prototype of the upper level control based on fuzzy logic was built. It optimises voltage setpoints by the help of temperature measurements and gives instructions for right time material additions and for right ending time of the melting. Tuning of the controller was experimentally made by trial and error method. Testing of the controller was done off-line without feedback of the process. Testing results were good. It will easily be possible to develop the prototype controller further to the industrial use.

A Comparison of Different Control Strategies of a Rotary Drier

Abstract This paper presents control results for a rotary drier given by a conventional feedback control, control based on material and energy balances and by a state control. The results are presented separately and a comparison of these different control strategies is made. The comparison is based on the simulations with an Eclipse S/140 computer and on the experiments carried out with a pilot-plant rotary drier.

Process Control via Network

The explosive growth in the area of computing and networking has occurred. This has caused an increased reliance on distributed computing and process operations across the networks. The main aspect in the process control across network is the network delay, which depends on the network type and protocol. This paper gives the literature review about the network-based control systems and the methods developed for handling and compensating the network delay in a control loop. In the experimental part the research environment for examining the control performance of a laboratory-scaled process across three different wired networks and wireless ad-hoc network is described and the control results are compared. The wired networks are Ethernet, Internet and FUNET, which is the network operating between the universities in Finland. This means that the distances between the operator and the process to be controlled vary remarkably from twenty meters to several hundred kilometers. Also the transmission speed of the network is different. The network delays are measured and compared with each other. Also the loss of data packages in different networks is examined.