  The objective of this work is to optimize the performance of a constant flow
parallel mechanical displacement micropump, which has parallel pump chambers
and incorporates passive check valves. The critical task is to minimize the
pressure pulse caused by regurgitation, which negatively impacts the constant
flow rate, during the reciprocating motion when the left and right pumps
interchange their role of aspiration and transfusion. Previous works attempt to
solve this issue via the mechanical design of passive check valves. In this
work, the novel concept of overlap time is proposed, and the issue is solved
from the aspect of control theory by implementing a RBF neural network trained
by both unsupervised and supervised learning. The experimental results indicate
that the pressure pulse is optimized in the range of 0.15 - 0.25 MPa, which is
a significant improvement compared to the maximum pump working pressure of 40
MPa.
