AN EXPERT SYSTEM FOR SYSTEM IDENTIFICATION

An expert system for system identification written with the OPS83 knowledge-based programming language is presented. At the end of an expertise, it provides the user with a set of good models for the system under investigation. If the sampling period used to collect the data seems to be unadapted, the expert system will modify it. An intelligent search through the set of all admissible models is made in order to find the best models of the system. Some validation criteria are used to classify the models and a complete set of facilities is at the user's disposal that allows to modify the expert system behaviour at execution time. One advantage of the expert system approach is that one can not only change decision parameters very easily (such as confidence levels) but one can also change existing rules or add new rules at the price of only one more compilation. Finally, some simulations on data from industrial processes have shown that the expert system behaves just as well as human experts while on simulated noisy data, it finds the true model in the class of ARX or ARARX (also called GLS) models that was used to produce them.