Abstract:
In automatic control system of a chemical process, tens or hundreds of control
loops are used in a multiloop control con guration. Loop interaction arises in
these loops when changes are made in one of the parameters of the control loops.
It is di cult to measure the degree of interactions between the control loops and
rank the loops according to their extent of interactions.
This study presents two novel data driven techniques to determine control loop
interactions and rank the loops according to their importance. In rst approach,
two new indices have been developed using integral of absolute or squared error
(IAE or ISE) criteria to quantify loop interaction and determine rank of the loops.
The rst index calculate the presence of interaction from one loop to another using
IAE or ISE of the two interacting loops. Then by using these loop interaction
values a loop interaction matrix has been formed. The second index uses the loop
interaction matrix to calculate the rank of the loops.
In another approach, a novel method based on canonical correlation analysis has
been developed to calculate interaction among the loops. An index has been
proposed in this method to determine the ranking of the loops and the ranking
has been done with respect to the maximum canonical correlation value of the
control loops.
The proposed methods have been evaluated using both simulation and experimental
studies. Both simulation and experimental results demonstrate the validity and
e cacy of the proposed methods.
