The Importance of Control Engineering in Automation
•Device Development in Industrial Control Engineering
•Functional Development of Industrial Control Systems
•From More Complex Control Procedures to Advanced Control
•Fields of Application of Industrial Control Engineering
•Conclusion and Outlook
Control engineering, as one of the cornerstones of automation, has contributed enormously to the development of modern industrial society. In the automation systems of today, control engineering remains one of the core functions. It ultimately enables actual automation tasks to be accomplished, even though the controllers themselves are not as immediately obvious to the observer as modern user interfaces. Yet, control engineering still delivers a considerable proportion of the benefit customers gain from automation systems.
The job of the controller is essentially to capture process variables -- either as a continuous process or at sufficiently short intervals -- and to compare them with set values. The controller uses the results of the comparison as the basis for intervention in the process being controlled, thus ensuring that in a steady state, process variables are in line with specified set values.
Controllers are therefore important for the running of a technical plant when the process to be managed is subject to influences that, without control, would cause the process variables to deviate from the set values. Where a technical process is to run automatically, the use of controllers is vital with respect to economy, reproducibility of product quality, service quality, safety and environmental protection.
In order to keep meeting these criteria, technical plant operators are forced to continuously improve automation systems, which has also had a knock-on effect on the development of industrial control systems. Particularly over the last decade, a vast range of various control functions — the like of which control theorists could long only dream of — have emerged in industrial systems to join the classic PID controller. A PID controller calculates its output signal by a proportional, integral and differential process in relation to the input signal.
Although controllers that use a more sophisticated procedure than the PID algorithm are only used in relatively few processes, there is a particular benefit in the fact that, with processes that are difficult to control, better control performance or at least automatic control can be achieved.
Device Development in Industrial Control Engineering
Originally, control systems took the form of mechanical controllers, such as the centrifugal governor on a steam engine, which ensured the engine turned over at a defined speed, despite a variable load. The key properties of mechanical controllers can easily be deduced from this example:
- Mechanical controllers are process-specific entities.
- The variables processed by the controller are of a mechanical nature and are process-specific.
- The necessary auxiliary energy is generally taken directly from the process itself.
- Mechanical controllers usually display non-linear behavior. Parameterization is accomplished by making mechanical adjustments on the controller.
- The mechanical controller usually combines a device for capturing the control variable, the controller and the actuator.
When pneumatics arrived on the scene, control engineering underwent swift development, characterized primarily by the following properties: unit signals (0 to 1 bar or 0.2 to 1 bar) enable different measurement, control, adjustment and display devices to be combined at will. This results in universally usable standard components and modular systems. Measurement, control and adjustment functions are allocated to separate devices.
The core component of the pneumatic controller, the nozzle-baffle-amplifier, makes it easier to produce different controller algorithms and to parameterize them.
This development continued with electric and electronic controllers, with standard signals and amplifier components playing a crucial role in simplifying implementation and application. In addition to this, however, there was an emphasis on miniaturization of automation components and the improvement in service quality achieved by replacing high-wear mechanical parts with electronics, which was accompanied by a reduction in manufacturing costs.
Today, controllers invariably take the form of software controllers incorporated into digital devices and systems. The advantages over earlier technologies lie in the flexibility with respect to algorithms, the accuracy of parameterization, and, once again, the lower cost per controller.
However, all the technologies described have remained in use to this day for applications where they have proven to be of particular customer benefit. Examples include:
- Mechanical pressure controllers in gas and water distribution networks. These controllers are simple, robust and perform their function without requiring a separate source of auxiliary energy.
- Pneumatic actuators are valued for their "natural" explosion-proof properties.
- Electronic controllers are used for very high-speed processes, for example to regulate the current on electric drive mechanisms, because they work continuously.
Functional Development of Industrial Control Systems
PID controllers
The vast majority of applications in industrial automation are still dominated by PID controllers. These continue to offer the benefit of ease of use and high robustness. It is precisely these aspects that matter in standard applications, as the operator of an industrial plant, who usually only has a few staff with control system expertise, wants the control loop, once in place, to function properly for many years to come.
Nevertheless, there have been a number of advances in PID controllers in recent years. Many compact controllers and automation systems today feature adaptation algorithms or adaptation tools that enable the controller to be easily and reliably optimized for the particular process. This means reduced time for system set-up and increased control quality compared with empirical controller optimization.
PID controllers, which are predominantly available in software form, can be regarded as distributed automation objects, consisting of the controller function component that is cyclically processed in the automation device, the operator interface of the controller in the operating and monitoring system and the usually graphic representation of the controller function component in the engineering system.
In an industrial PID controller function component, the actual controller algorithm only accounts for 10% to 20% of the functionality. In addition to the core functions, the controller performs a number of extra functions. It is these that equip the controller to cope with industrial applications, and nowadays it is these that make the difference between products from different manufacturers. Examples include:
- standardization of control variables, set values, correcting variables;
- monitoring of control variables, deviations, parameters;
- filtering of control variables, deviations;
- mode selection and limitation of operator intervention;
- correcting variable limits;
- different formats of controller output: continuous, switching and three-point.
From More Complex Control Procedures to Advanced Control
Controllers for specific control tasks include dead-time controllers that mostly use the Smith predictor as a basis. One or more PID controllers can be combined with extra functions to produce more complex structures like cascade controllers, ratio controllers and split range controllers that are increasingly coming onto the market as complete modules.
In processes with very high time constants, highly non-linear behavior or significant interaction, there are limits beyond which PID controllers can no longer guarantee the required control quality or bring about stable behavior. Whereas, in the past, such processes were controlled by constant or at least regular manual intervention by plant staff, or could only be managed by developing special controllers for the specific application, today many standard automation systems already feature a whole host of new functions. These include multivariable controllers, status controllers, fuzzy control and neuronal networks.
Fields of Application of Industrial Control Engineering
Controllers are conventionally used for directly controlling process variables such as pressure, temperature, flow rate, filling level, speed, position etc. The majority of applications involve using these controllers for process-related functions of this sort, and this is also the domain of the PID controller. It is available mostly in the form of compact controllers, programmable logic controllers (PLCs) and process control systems (PCSs) in the process control layer, but also in all other layers of the conventional automation hierarchy.
Field layer
Here, control functions are increasingly being integrated into field devices. Two main categories can be distinguished.
Automatic control functions, such as position controllers in actuating drives or speed controllers in drive mechanisms, which enable the field device to function or which add to its range of functions. And in many areas, adaptive controllers are coming onto the scene which make it easier to get the field device up and running and ensure that it functions properly in the long run. Process controllers, mostly PID controllers, make it possible to directly control a process variable through such means as an "intelligent" actuator for example.
Process Control Layer
Most of the automatic control functions are still found in the process control layer. Process-related PID controllers, but increasingly also more sophisticated control functions like multivariable controllers, fuzzy control etc., are available as standard function modules for many PLCs and PCSs. The catalogue of automatic control functions available for PLCs has grown considerably in the last few years. So even with processes that are difficult to control, it is usually possible to achieve satisfactory automatic operation. Much the same thing applies to PC-based automation systems.
Plant Management Layer
Whereas in the lower layers of automation engineering, direct control of process variables in relation to constant or variable set values is the key aim, in the higher automation layers, control engineering contributes to optimizing processes. Optimization measures may, for example, be designed to increase cost-efficiency, achieve reproducible product quality or reduce environmental impact by lowering emissions or cutting raw materials/energy consumption.
These applications increasingly use multivariable controllers, and also fuzzy control and neuronal networks, which fulfill an optimizing or coordinating function with respect to whole plant sections or the entire process.
The controllers in this automation layer intervene in the process by specifying optimal set values for the controllers in the subordinate automation layers. These controllers generate a high degree of customer utility, as we can see from the above examples.
Control engineering as a whole is constantly being enhanced with new functions, driven by the increasing need for continuous improvement of economic and ecological factors and conditions, as well as output quality and plant safety. These new automatic control functions are founded both on the accepted theoretical principles of control engineering and on the principles of data processing. Modern hardware and software are enabling more and more viable functions and tools to be produced which are easy to use, even for someone without any great theoretical knowledge.
At the same time, control engineering is increasingly penetrating areas of the automation hierarchy where, in the past, there was no role for it or only a limited one. Worth mentioning above all are new automatic control functions in field devices, which improve their functionality, and in the plant management layer, where control engineering is bringing fresh impetus to the optimization of production plants.
Control engineering is also expected to contribute to improving business processes: although "controlling" is familiar term in this context, actual control engineering methods and procedures have yet to be implemented to any degree.
Edmund Linzenkirchner (Dipl.-Ing.) works in pre-field development in the Automation & Drives (A&D) division of Siemens AG, where he is responsible for the development of state-of-the-art automation processes.
Article courtesy of Interkamma '99, Dusseldorf, Germany October 18-23, 1999.