The effectiveness of proportional-integral-derivative (PID)
controllers for a large class of process systems has ensured their
continued and widespread use in industry. Similarly there has been
a continued interest from academia in devising new ways of
approaching the PID tuning problem.
To the industrial engineer and many control academics this work
has previously appeared fragmented but a key determinant of this
literature is the type of process model information used in the PID
tuning methods. PID Control presents a set of coordinated
contributions illustrating methods, old and new, that cover the
range of process model assumptions systematically. After a review
of PID technology, these contributions begin with model-free
methods, progress through non-parametric model methods (relay
experiment and phase-locked-loop procedures), visit fuzzy-logic-
and genetic-algorithm-based methods; introduce a novel subspace
identification method before closing with an interesting set of
parametric model techniques including a chapter on predictive PID
controllers.
Highlights of PID Control include:
- an introduction to PID control technology features and typical
industrial implementations;
- chapter contributions ordered by the increasing quality of the
model information used;
- novel PID control concepts for multivariable processes.
PID Control will be useful to industry-based engineers wanting a
better understanding of what is involved in the steps to a new
generation of PID controller techniques. Academics wishing to have
a broader perspective of PID control research and development will
find useful pedagogical material and research ideas in this
text.
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