Observation and identification tools for non-linear systems: application to a fluid catalytic cracker

In this paper we recall general methodologies we developed for observation and identification in non-linear systems theory, and we show how they can be applied to real practical problems.

In a previous paper, we introduced a filter which is intermediate between the extended Kalman filter in its standard version and its high-gain version, and we applied it to certain observation problems. But we were missing some important cases. Here, we show how to treat these cases.

We also apply the same technique in the context of our identifiability theory.

As non-academic illustrations, we treat a problem of observation and a problem of identification, for a fluid catalytic cracker (FCC). This FCC unit is one of the most crucial from an economic point of view for the petroleum industry.