Studies on On-line State and Parameter Estimation through a Real-time Process Simulator

Abstract

A PC-based simulator of non-linear multiple-input multiple-output dynamic systems was employed for studies concerning the on-line estimation of both 'non-measured' state variables and multiple specific growth rates of a virtual baker´s yeast fed-batch fermentation. The identification algorithms were implemented in an 'Observer Computer' which received, optionally in 'real-time', in 'scaled time' or in 'simulation time', the 'measured' state variables generated by the process simulator in the 'Process Computer'. The state observer showed a robust behaviour under different situations where process parameters, operating variables and measuring characteristics (noise and delays) were changed in the process computer. The simulation package was seen to be an efficient and cheap tool for the simulation of non-linear processes with time varying parameters, providing a realistic environment for tests of identification, estimation and control strategies.

Stability, dynamics of convergence and tuning of observer-based kinetics estimators

“…The results and conclusions of the preceding sections are now illustrated with an application to a baker's yeast cultivation process. The process data were obtained by simulation, using the dynamical model for the fed-batch fermenter described by Feyo de Azevedo et al [17].…”

Model-Based Estimation of Reaction Rates in Stirred Tank Bioreactors

“…The reaction rates ϕ are most often complex functions of the operating conditions and of the state of the process. Situations like 'unknown (some or all) yield coefficients', or 'unknown or partially known kinetic models' are extensively studied and discussed in the literature (Bastin and Dochain, 1990;Pomerleau and Perrier, 1990;Feyo de Azevedo et al, 1992). The construction of a suitable kinetic model may constitutes a difficult task, if not an impossible one.…”