A complete solution can require hundreds of such rules to cover all possible situations it may encounter AND all functions that will be required. In any case, a rule-based system executes the entire rule set at periodic intervals to determine what is to be done next.
In general, rule-based systems can be divided into two broad cat
egories: fuzzy logic systems and expert systems. Both approaches provide a means to incorporate non-mathematical concepts and conditions into a control solution. Fuzzy logic systems are a hybrid of mathematical and non-mathematical concepts. Expert systems are almost always developed in an environment designed for language processing.
There are many good references on the details and techniques of fuzzy logic control and expert systems. The following link provides a listing of general sources of fuzzy information and research groups: https://www.cse.dmu.ac.uk/~rij/general.
Fuzzy logic concepts
Very often, human perceptions and judgments are not precise. A typical human thought might be a conditional statement such as:
‘If the product temperature is low, and throughput is low, then open the steam valve a small amount. If the product temperature is low and the throughput is high, then open the valve a larger amount.’
Such a statement contains several imprecise concepts,¡ªfor example, ‘low’ and ‘large,’ which become precise for humans through experience. Fuzzy logic is the approach that has been developed to use this kind of rule in process control systems that do not have the benefit of experience.
Changing constants is one way to fine tune fuzzy logic control system performance. In the end, something specific has to be done. The basic contribution of fuzzy logic techniques is to integrate fuzzy decision concep
