Timetable:

Begin: 2000-01-01

End: 2003-05-01

Description:

The number of control loops used in industry is growing continuously and there are problems in keeping them well tuned. In order to ensure highest product quality it is essential to maintain the control systems in an adequate manner. An improved control performance has a considerable effect on variations in end product quality, and thus on the productivity of the plant. Additional benefits are low consumption of raw materials and energy, as well as a longer life span of the instruments. During the last decades considerable effort has been placed on developing suitable indices for evaluating control performance. The evaluation methods can be divided into two categories: stochastic and deterministic methods. The most widely studied stochastic indices are those based on using of MVC (minimum variance controller) calculation as a benchmark. Deterministic indicators are more informative in the case of a sudden load disturbance or a set point change. Various dimensionless indices for setpoint changes have been proposed in the literature.
Different kinds of indices were tested using a flotation cell process model that was programmed in Matlab Simulink toolbox. Indices that functioned well in the simulations, and which were applicable to on-line monitoring, were chosen for further development.
The indices were implemented using the GE Fanuc CIMPLICITY HMI Plant Edition and its script language. Cimplicity is a user interface program for process control, and is widely used in flotation processes. Outokumpu pilot Tankcell and the above-mentioned programs were to test the indices in practice. The cell instruments were connected to the Foundation Fieldbus an controlled by Smar DFI 302. The controller unit was connected via Ethernet to the OPC(OLE(Object Linking and Embedding) for process Control ) server, and Cimplicity used the OPC port to control the flotation cell.
Simulations and tests performed with the pilot flotation cell proved that the indices provided the necessary information about the control performance. This monitoring tool could be used in plants to monitor the key controllers for improving process control and product quality. More attention will be paid to the economical effects in the future research.

Researchers:

Risto Poikonen
Zdravko Georgiev
Ursula Zuehlke

             This info last modified 2005-08-15 by Jerri Kämpe-Hellenius