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.</P>

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. <STRONG>PID Control</STRONG> 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.</P>

Highlights of <STRONG>PID Control</STRONG> include: </P> <UL> <LI>an introduction to PID control technology features and typical industrial implementations; </LI> <LI>chapter contributions ordered by the increasing quality of the model information used;</LI> <LI>novel PID control concepts for multivariable processes. </LI></UL>

<STRONG>PID Control</STRONG> 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.</P>