The PID controller has several important functions: it provides feedback; it has the ability to eliminate steady state offsets through integral action; it can anticipate the future through derivative action. PID controllers are sufficient for many control problems, particularly when process dynamics are benign and the performance requirements are modest. PID controllers are found in large numbers in all industries. The controllers come in many different forms. There are standalone systems in boxes for one or a few loops, which are manufactured by the hundred thousands yearly. PID control is an important ingredient of a distributed control system. The controllers are also embedded in many special-purpose control systems. In process control, more than 95% of the control loops are of PID type, most loops are actually PI control. Many useful features of PID control have not been widely disseminated because they have been considered trade secrets. Typical examples are techniques for mode switches and anti-windup.

PID control is often combined with logic, sequential machines, selectors, and simple function blocks to build the complicated automation systems used for energy production, transportation, and manufacturing. Many sophisticated control strategies, such as model predictive control, are also organized hierarchically. PID control is used at the lowest level; the multivariable controller gives the setpoints to the controllers at the lower level. The PID controller can thus be said to be the "bread and butter" of control engineering. It is an important component in every control engineer's toolbox.

PID controllers have survived many changes in technology ranging from pneumatics to microprocessors via electronic tubes, transistors, integrated circuits. The microprocessor has had a dramatic influence on the PID controller. Practically all PID controllers made today are based on microprocessors. This has given opportunities to provide additional features like automatic tuning, gain scheduling, and continuous adaptation. The terminology in these areas is not well-established. For purposes of this book, auto-tuning means that the controller parameters are tuned automatically on demand from an operator or an external signal, and adaptation means that the parameters of a controller are continuously updated. Practically all new PID controllers that are announced today have some capability for automatic tuning. Tuning and adaptation can be done in many different ways. The simple controller has in fact become a test bench for many new ideas in control.

The emergence of the fieldbus is another important development. This will drastically influence the architecture of future distributed control systems. The PID controller is an important ingredient of the fieldbus concept. It may also be standardized as a result of the fieldbus development.

A large cadre of instrument and process engineers are familiar with PID control. There is a well-established practice of installing, tuning, and using the controllers. In spite of this there are substantial potentials for improving PID control. Evidence for this can be found in the control rooms of any industry. Many controllers are put in manual mode, and among those controllers that are in automatic mode, derivative action is frequently switched off for the simple reason that it is difficult to tune properly. The key reasons for poor performance is equipment problems in valves and sensors, and bad tuning practice. The valve problems include wrong sizing, hysteresis, and stiction. The measurement problems include: poor or no anti-aliasing filters; excessive filtering in "smart" sensors, excessive noise and improper calibration. Substantial improvements can be made. The incentive for improvement is emphasized by demands for improved quality, which is manifested by standards such as ISO 9000. Knowledge and understanding are the key elements for improving performance of the control loop. Specific process knowledge is required as well as knowledge about PID control.

Based on our experience, we believe that a new era of PID control is emerging. This book will take stock of the development, assess its potential, and try to speed up the development by sharing our experiences in this exciting and useful field of automatic control. The goal of the book is to provide the technical background for understanding PID control. Such knowledge can directly contribute to better product quality.

Process dynamics is a key for understanding any control problem. Chapter 2 presents different ways to model process dynamics that are useful for PID control. Methods based on step tests are discussed together with techniques based on frequency response. It is attempted to provide a good understanding of the relations between the different approaches. Different ways to obtain parameters in simple transfer function models based on the tests are also given. Two dimension-free parameters are introduced: the normalized dead time and the gain ratio are useful to characterize dynamic properties of systems commonly found in process control. Methods for parameter estimation are also discussed. A brief description of disturbance modeling is also given.

An in depth presentation of the PID controller is given in Chapter 3. This includes principles as well as many implementation details, such as limitation of derivative gain, anti-windup, improvement of set point response, etc. The PID controller can be structured in different ways. Commonly used forms are the series and the parallel forms. The differences between these and the controller parameters used in the different structures are treated in detail. Implementation of PID controllers using digital computers is also discussed. The underlying concepts of sampling, choice of sampling intervals, and antialiasing filters are treated thoroughly. The limitations of PID control are also described. Typical cases where more complex controllers are worthwhile are systems with long dead time and oscillatory systems. Extensions of PID control to deal with such systems are discussed briefly.

Chapter 4 describes methods for the design of PID controllers. Specifications are discussed in detail. Particular attention is given to the information required to use the methods. Many different methods for tuning PID controllers that have been developed over the years are then presented. Their properties are discussed thoroughly. A reasonable design method should consider load disturbances, model uncertainty, measurement noise, and set-point response. A drawback of many of the traditional tuning rules for PID control is that such rules do not consider all these aspects in a balanced way. New tuning techniques that do consider all these criteria are also presented.

The authors believe strongly that nothing can replace understanding and insight. In view of the large number of controllers used in industry there is a need for simple tuning methods. Such rules will at least be much better than "factory tuning," but they can always be improved by process modeling and control design. In Chapter 5 we present a collection of new tuning rules that give significant improvement over previously used rules.

In Chapter 6 we discuss some techniques for adaptation and automatic tuning of PID controllers. This includes methods based on parametric models and nonparametric techniques. A number of commercial controllers are also described to illustrate the different techniques. The possibilities of incorporating diagnosis and fault detection in the primary control loop is also discussed.

In Chapter 7 it is shown how complex control problems can be solved by combining simple controllers in different ways. The control paradigms of cascade control, feedforward control, model following, ratio control, split range control, and control with selectors are discussed. Use of currently popular techniques such as neural networks and fuzzy control are also covered briefly.

References

A treatment of PID control with many practical hints is given in (Shinskey, 1988). There is a Japanese text entirely devoted to PID control by (Suda et al, 1992). Among the books on tuning of PID controllers, we can mention (McMillan, 1983) and (Corripio, 1990), which are published by ISA.

There are several studies that indicate the state of the art of industrial practice of control. The Japan Electric Measuring Instrument Manufacturers' Association conducted a survey of the state of process control systems in 1989, see (Yamamoto and Hashimoto, 1991). According to the survey more than than 90% of the control loops were of the PID type.

The paper, (Bialkowski, 1993), which describes audits of paper mills in Canada, shows that a typical mill has more than 2000 control loops and that 97% use PI control. Only 20% of the control loops were found to work well and decrease process variability. Reasons for poor performance were poor tuning (30%) and valve problems (30%). The remaining 20% of the controllers functioned poorly for a variety of reasons such as: sensor problems, bad choice of sampling rates, and anti-aliasing filters. Similar observations are given in (Ender, 1993), where it is claimed that 30% of installed process controllers operate in manual, that 20% of the loops use "factory tuning," i.e., default parameters set by the controller manufacturer, and that 30% of the loops function poorly because of equipment problems in valves and sensors.