Thereare richtheories and designs for generalcontrolsystems,but usually, they will not lead to PID controllers. Noting that the PID controller has been the most popular one in industry for over ?fty years, we will con?ne our discussion hereto PIDcontrolonly. PID controlhasbeenanimportantresearchtopicsince 1950’s, and causes remarkable activities for the last two decades. Most of the existing works have been on the single variable PID control and its theory and design are well established, understood and practically applied. However, most industrial processes are of multivariable nature. It is not rare that the overall multivariable PID control system could fail although each PID loop may work well. Thus,demandforaddressingmultivariableinteractionsishighforsuccessful applicationofPIDcontrolinmultivariableprocessesanditisevidentfrommajor leading control companies who all rankedthe couplings of multivariable systems as the principal common problem in industry. There have been studies on PID control for multivariable processes and they provide some useful design tools for certaincases. But itis notedthat the existing worksaremainlyfor decentralized form of PID control and based on ad hoc methodologies. Obvious, multivariable PID control is much less understood and developed in comparison with the single variable case and actual need for industrial applications. Better theory and design have to be established for multivariable PID control to reach the same maturity and popularity as the single variable case. The present monograph puts together, in a single volume, a fairly comp- hensive, up-to-date and detailed treatment of PID control for multivariable p- cesses, from paring, gain and phase margins, to various design methods and applications.

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.

The field of process control has evolved gradually over the years, with emphasis on key aspects including designing and tuning of controllers. This textbook covers fundamental concepts of basic and multivariable process control, and important monitoring and diagnosis techniques. It discusses topics including state-space models, Laplace transform to convert state-space models to transfer function models, linearity and linearization, inversion formulae, conversion of output to time domain, stability analysis through partial fraction expansion, and stability analysis using Routh table and Nyquits plots. The text also covers basics of relative gain array, multivariable controller design and model predictive control. The text comprehensively covers minimum variable controller (MVC) and minimum variance benchmark with the help of solved examples for better understanding. Fundamentals of diagnosis of control loop problems are also explained and explanations are bolstered through solved examples. Pedagogical features including solved problems and unsolved exercises are interspersed throughout the text for better understanding. The textbook is primarily written for senior undergraduate and graduate students in the field of chemical engineering and biochemical engineering for a course on process control. The textbook will be accompanied by teaching resource such a collection of slides for the course material and a includsolution manual for the instructors.

Process Identification and PID Control enables students and researchers to understand the basic concepts of feedback control, process identification, autotuning as well as design and implement feedback controllers, especially, PID controllers. The first The first two parts introduce the basics of process control and dynamics, analysis tools (Bode plot, Nyquist plot) to characterize the dynamics of the process, PID controllers and tuning, advanced control strategies which have been widely used in industry. Also, simple simulation techniques required for practical controller designs and research on process identification and autotuning are also included. Part 3 provides useful process identification methods in real industry. It includes several important identification algorithms to obtain frequency models or continuous-time/discrete-time transfer function models from the measured process input and output data sets. Part 4 introduces various relay feedback methods to activate the process effectively for process identification and controller autotuning. Combines the basics with recent research, helping novice to understand advanced topics Brings several industrially important topics together: Dynamics Process identification Controller tuning methods Written by a team of recognized experts in the area Includes all source codes and real-time simulated processes for self-practice Contains problems at the end of every chapter PowerPoint files with lecture notes available for instructor use

Master Process Control Hands On, through Updated Practical Examples and MATLAB® Simulations Process Control: Modeling, Design, and Simulation, Second Edition, is a complete introduction to process control and has been fully updated, integrating current software tools to enable professionals and students to master critical techniques hands on through simulations based on modern versions of MATLAB. This revised edition teaches the field's most important techniques, behaviors, and control problems with even more practical examples and exercises. Wide-ranging enhancements include safety considerations, an expanded discussion of digital control, additional process examples, and updates throughout for newer versions of MATLAB and SIMULINK. Fundamentals of process control and instrumentation, including objectives, variables, block diagrams, and process flowsheets Methodologies for developing dynamic models of chemical processes, including compartmental models Dynamic behavior of linear systems: state-space models, transfer function-based models (including conversion to state space), and more Empirical and discrete-time models, including relationships among types of discrete models Feedback control; proportional, integral, and derivative (PID) controllers; and closed-loop stability analysis Frequency response analysis techniques for evaluating the robustness of control systems Improving control loop performance: internal model control (IMC), automatic tuning, gain scheduling, and enhanced disturbance rejection Split-range, selective, and override strategies for switching among inputs or outputs Control loop interactions and multivariable controllers An introduction to model predictive control (MPC), with a new discrete state-space model derivation exercise Bequette walks step by step through developing control instrumentation diagrams for an entire chemical process, reviewing common control strategies for individual unit operations, then discussing strategies for integrated systems. This edition also includes 16 learning modules demonstrating how to use MATLAB and SIMULINK to solve many key control problems, including new modules on process monitoring and safety, as well as a detailed new study of artificial pancreas systems for Type 1 diabetes. Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.

The new 4th edition of Seborg’s Process Dynamics Control provides full topical coverage for process control courses in the chemical engineering curriculum, emphasizing how process control and its related fields of process modeling and optimization are essential to the development of high-value products. A principal objective of this new edition is to describe modern techniques for control processes, with an emphasis on complex systems necessary to the development, design, and operation of modern processing plants. Control process instructors can cover the basic material while also having the flexibility to include advanced topics.