The industrial evidence is that for many control problems, particularly those of the process industries, theProportional, Integral andDerivative(PID) controller is themaincontrol tool beingused. Forthese industrial problems, the PID control module is a building block which provides the regulation and disturbance rejection for single loop, cascade, multi-loop and multi-input multi-output control schemes. Over the decades, PID control technology has undergone many changes and today the controller may be a standard utility routine within the supervisory system software, a dedicated ha- ware process controller unit or an input-output module within a programmable electronic system which can be used for control system construction. With such a well-developed industrial technology available it is not surprising that an academic colleague on learning that we planned a book on PID control exclaimed, "Surely not Is there anything left to be said?." Of course, the short answer is that technology does not stand still: new solution capab- ities are always emerging and PID control will evolve too. Indeed, the Ziegler-Nichols rules have been famous for over sixty years and the Astrom and Hagglund relay experiment has been around for twenty years, so it would be disappointing if some new approaches to PID control had not emerged in the me- time."

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.