Adaptive multirate state and parameter estimation strategies with application to a bioreactor

Abstract

Abstract The design and development of a mu8ltirate software sensor for use in the chemical process industry are presented. The measurements of process outputs that arrive at different sampling rates are formally accommodated into the estimation strategy by using rhwe multirate formulation of the iterated extended kalman filter. Measurement delays associated with some of the process outputs are included in the system description by addition of delayed states. Observability issues associated with state and parameter estimation in a multirate framework are discussed and modified measurement equations are proposed for systems with delayed measurements to ensure relatively “strong” system observability. The evaluation of the proposed multirate state and parameter estimator through simulations and an experimental application on afed batch fermentation system gave satisfactory performance.