CONTROL OF A PULSED LIQUID-LIQUID EXTRACTION COLUMN BASED ON A MULTILEVEL SYSTEM OF AUTOMATA

This paper presents the real-time application of the learning control theory to the control of a chemical pilot plant: a pulsed liquid-liquid extraction column.

The behaviour of an agitated liquid-liquid extraction column can be related to random mechanisms such as the phenomena of droplets breakage and coalescence. Previous studies on hydrodynamic and mass transfer aspects showed that a pulsed liquid-liquid extraction column had an optimal behaviour for operating conditions close to flooding. These results led to choose the following strategy to control the column in its optimal behaviour zone:

- the measure of the conductivity of the liquid medium below the distributor which gives a good information about flooding, is the controlled variable

-the pulse frequency is the control action.

The learning control algorithm is based on a multilevel system of automata which operates in a random environment. By means of an evaluation unit of the performances of the column which generates either penalty (inaction) or reward on the basis of heuristic rules, the automaton chooses a value of the pulse frequency. This approach is essentially connected to artificial intelligence in so far as human knowledge on the plant is included in these rules.

This algorithm has been implemented on a microcomputer for control purposes. The experimental results presented show the good performances of the approach.