Abstract
A two-dimensional nonlinear distributed-parameter optimal state estimation
algorithm has been developed and applied to an exothermic packed
bed catalytic reactor. Temperature and concentration profiles were
estimated from limited temperature and/or concentration measurements.
Orthogonal collocation was used to solve the differential sensitivity
and filtering equations. Both simulations and on-line experiments
with a pilot scale packed bed reactor for the partial oxidation of
methanol have been used to study the effects of measurement choice,
model parameter errors, and unmeasured process disturbances. Excellent
tracking of the reactor profiles was achieved with only one or two
properly placed temperature sensors.
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