The first-order plus
time delay (FOPTD) model-based method is a
standard approach to tune proportional–integral (PI) controllers
in plants. The FOPTD model can be obtained easily from step responses.
However, because of their structural limitations, FOPTD models suffer
from difficulties in approximating step responses for some processes
including processes with overshoot, resulting in PI controllers with
unacceptable performance. To remove these drawbacks, models combining
two FOPTD models that can be obtained easily from step responses are
proposed to tune PI controllers. Several simulations and experimental
examples are given, illustrating the improved performance of the proposed
method.
Many
methods are available to tune proportional integral (PI) controllers
for first order plus time delay (FOPTD) models of overdamped processes.
The two asymptotes for small and large ratios of time delays over
time constants are easily calculated. These two asymptotes can be
used to evaluate and provide guidelines for the performance and application
ranges of PI controller tuning rules. By matching these two asymptotes,
a simple analytic tuning rule is suggested. For some overdamped processes
whose transfer functions have large zero terms, half-order plus time
delay (HOPTD) models are found to yield better results than the FOPTD
models. Applying the technique of matching two asymptotes, a simple
analytic PI controller tuning rule has also been proposed for the
HOPTD models. To apply these tuning rules to high order processes
with known transfer functions, model reduction methods to obtain the
FOPTD and HOPTD models are investigated. Simulation results for empirical
and full models of processes show the performances of the proposed
model reduction methods and tuning rules.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.