Software sensor design for COD estimation in an anaerobic fluidized bed reactor

in this paper, a method for unknown input estimation in stochastic system i s presented. A key problem in bioprocess systems is the absence, in some ca ses, of reliable on-line measurements for real time monitoring applications . In this paper, a software sensor for an anaerobic digester is presented. Unmeasured components of the influent are estimated from available on-line measurements. Unknown input Kalman filter is discussed to estimate the stat e and unknown input of the process. First, the theory of unknown inputs opt imal filtering in the stochastic case is exposed and a design procedure is proposed. The observer is applied to an anaerobic fluidized bed reactor to estimate the variations in Chemical Oxygen Demand (COD) concentration and e xperimental results are presented.