Rule-based Reactor Control

Language rules can address control problems, especially if robust measurements are lacking. That's a fundamentally different approach to mathematical algorithms than those used in the three previous installments of this series.

Not all the variables need to be considered together, AND the set of all logical combinations can usually be broken down into more appropriate subsets.

Lew Gordon

 

AT A GLANCE

• Machine control
• Robots
• Machine vision
• Open architecture
• Signal conditioners

Using language rules to address control issues was borne of the need to deal with problems that resisted precise mathematical definition for one reason or another. Also, the traditional control technologies of basic regulatory control (BRC) and advanced regulatory control (ARC) discussed in the previous installments assume the availability of robust signals from field transmitters to provide the needed measurement values. But these signals are not always available, and the information they provide may be insufficient.

In addition, the absolute values of process variables are not the only key issue that must be considered. Rates of measurement change can be more important. Sometimes, the value or measurements have to be considered in relation to other conditions. Boolean logic states that conditions, such as whether process equipment is running or not, can be important. Proper control system operation also can depend on time of day, cleaning and maintenance, and other activities. Also, not all errors are equally important. Deviations in one direction may call for a weak or slow response, while deviations in another direction may require a strong or rapid response.

The bottom line is that a control problem can require several conditions to be considered in logical combinations. And all issues mentioned above can be difficult to express mathematically. In such cases, rule-based control can sometimes provide an advantage.

Rules, algorithms

At their core, dist