The
integration
of
design
and
control
of
chemical
processes
have
been
identified
as
a
key
area
of
research
and
many
methodologies
have
been
proposed
to
address
the
issue.
We
are
working
on
developing
a
new
methodology
for
integration
of
design
and
control
under
process
disturbances
and
parameter
uncertainty
using
Power
Series
Expansions
(PSE)
approximations.
The
key
idea
in
this
methodology
is
to
“back-off”
(move
away)
from
the
steady
state
design
(Figure
below
on
the
right),
which
might
be
infeasible
due
to
process
disturbances
and
parameter
uncertainty,
to
obtain
the
optimal
design
parameters
that
are
dynamically
feasible
at
low
economic
costs.
Each
process
constraint
and
the
cost
function
are
represented
using
PSE
approximations.
The
key
benefit
of
this
methodology
is
the
significant
reduction
in
the
computational
costs
associated
with
running
multiple
simulations
to
calculate
optimum
design
under
process
disturbances
and
parameter
uncertainty.
Thesis: Integration
of
Design
and
Control
under
Uncertainty:
A
New
Back-off
Approach
using
PSE
Approximations
