On-line state estimation of bioprocesses with full horizon observers

Software sensors (or state observers) are able to provide a continuous esti mation of some signals (e.g. concentrations of important culture components , like biomass) which are not measured by hardware sensors. They need a mat hematical model of the process and (discrete) hardware measurements of some other signals, like the concentrations of the main substrates. In this con tribution, the state observer (called full horizon observer) is based on th e identification of the most likely initial conditions of the experiment, e .g, the initial concentrations of the culture, these latter being identifie d at each time where new measurements are available. The basic principles o f this observer are given in the general framework of nonlinear systems. So me properties and extensions of this state estimation method are presented. Some comparisons with the linear and extended Kalman filters are also give n. The observer performances are illustrated in the case of the biomass con centration estimation within CHO animal cell cultures, for which only rare and asynchronous measurement samples of the glutamine, glucose and lactate concentrations are available. (C) 2001 IMACS. Published by Elsevier Science B.V. All rights reserved.