PID Control: New Identification and Design Methods
J. Crowe, K.K. Tan, T.H. Lee, R. Ferdous, M.R. Katebi, H.-P. Huang, J.-C. Jeng, K.S. Tang, G.R. Chen, K.F. Man, S. Kwong, A. Sánchez, Q.-G. Wang, Yong Zhang, Yu Zhang, P. Martin, M.J. Grimble, D.R. Greenwood (auth.), Michael A. Johnson PhD, Mohammad H. MoThe 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.