Data validation in large scale steady state linear systems

Mohamed Darouach (1) , José Ragot (1) , Jean Fayolle (1) , Didier Maquin (1)

1 CRAN - Centre de Recherche en Automatique de Nancy

The problem of data validation in large scale steady state linear systems is addressed. The system is described by algebraic equations. The conditions for observability and redundancy are defined and a procedure is presented for classifying the system variables into observable, unobservable, redundant and no redundant variables. Reconciliation of the redundant process measurements is developed using a recurrent estimation technique which is well suited in real time data processing. An application of the method to material balances is presented.

Keywords: Data validation; observability; redundancy; mass balances; recurrent estimation technique

Domains: Automatic

Mohamed Darouach, José Ragot, Jean Fayolle, Didier Maquin. Data validation in large scale steady state linear systems. 12th IMACS World Congress on Scientific Computation, IMACS'88, Jul 1988, Paris, France. ⟨hal-00293576⟩