Chapters

An introduction to process control and instrumentation is presented in Chapter 1. The development and use of models is very important in control systems engineering. Fundamental models are developed in Chapter 2, including the steady-state solution and linearization to form state space models. Chapter 3 focuses on the dynamic behavior of linear systems, starting with state space models and then covering transfer function-based models in detail. Chapter 4 we cover the development of empirical models, including continuous and discrete transfer function models.

Chapter 5 provides a more detailed introduction to feedback control, developing the basic idea of a feedback system, proportional, integral, derivative (PID) controllers, and methods of analyzing closed-loop stability. Chapter 6 presents the Ziegler-Nichols closed-loop oscillation method for controller tuning, since the same basic concept is used in the automatic tuning procedures presented in Chapter 11. Frequency response analysis techniques, important for determining control system robustness, are presented in Chapter 7.

In recent years model-based control has lead to improved control loop performance. One of the clearest model-based techniques is internal model control (IMC), which is presented in Chapter 8. The PID controller remains the most widely used controller in industry; in Chapter 9 we show how to convert internal model controllers to classical feedback (PID) controllers.

In Chapter 10 the widely used cascade and feed-forward strategies are developed. Many control loops suffer from poor performance, either because they were not tuned well originally, or because the process is nonlinear and has changed operating conditions. Two methods of dealing with these problems, automatic tuning and gain scheduling, are presented in Chapter 11. The phenomenon of reset windup and the development of antireset windup strategies are also presented in Chapter 11.

Many control strategies must be able to switch between manipulated inputs or select from several measured outputs. Split-range, selective and override strategies are presented in Chapter 12. Process units contain many control loops that generally do not operate independently. The effects of these control-loop interactions are presented in Chapter 13. The design of multivariable controllers is developed in Chapter 14.

The development of the control instrumentation diagram for an entire chemical process is challenging and remains somewhat of an art. In Chapter 15 recycle systems are shown to cause unique and challenging steady-state and dynamic control problems. In addition, an overview of corporate-wide optimization and control problems is presented. Model predictive control (MPC) is the most widely applied advanced control strategy in industry. The basic step response model-based MPC method is developed in Chapter 16. This is followed by a discussion of the constrained version of MPC, and enhancements to improve disturbance rejection.