  The variations in feedstock characteristics such as moisture and particle
size distribution lead to an inconsistent flow of feedstock from the biomass
pre-processing system to the reactor in-feed system. These inconsistencies
result in low on-stream times at the reactor in-feed equipment. This research
develops an optimal process control method for a biomass pre-processing system
comprised of milling and densification operations to provide the consistent
flow of feedstock to a reactor's throat. This method uses a mixed-integer
optimization model to identify optimal bale sequencing, equipment in-feed rate,
and buffer location and size in the biomass pre-processing system. This method,
referred to as the hybrid process control (HPC), aims to maximize throughput
over time. We compare HPC with a baseline feed forward process control. Our
case study based on switchgrass finds that HPC reduces the variation of a
reactor's feeding rate by 100\% without increasing the operating cost of the
biomass pre-processing system for biomass with moisture ranging from 10 to
25\%. A biorefinery can adapt HPC to achieve its design capacity.
