Online parameter identification for continuous fluidized bed spray granulation with external sieve-mill cycle

Parametrization of process models is an important task and often the first step in process control and monitoring. For continuous fluidized bed spray granulation, being often described by population balance models parameter estimation is particularly challenging due to the infinite-dimensional state space. In this contribution a Lyapunov-based approach is used to derive the appropriate online parameter estimation laws for a fluidized bed spray granulation with external sieve-mill cycle.