Application of estimation techniques to batch reactors—III. Modelling refinements which improve the quality of state and parameter estimation

Abstract This study is concerned with modelling refinements which improve significantly the estimation (using extended Kalman filter) of the rate of heat production in batch chemical reactors. Several ways of modelling heuristic knowledge are illustrated both in simulations and experiments, for example the use of random-ramp models instead of random-walk models for drifting parameters, the use of dynamic variance terms for parameters and states which change at known time instants, the use of a dynamic perturbation collector and the use of simplified kinetic models for higher-order chemical kinetics.