Cereals processing technology

40 Cereals processing technology
predictive model is not suitable for the application and could not be considered
for real time process control.
Rule-based and fuzzy control
Rule-based control is used in situations where other control techniques are
inappropriate, for example where sufficient theoretical knowledge is not
available or historical data is not complete enough to enable the creation of
accurate models of process behaviour. Rules used in control systems can take
the form of language-based equalities or number-based equalities; for example,
‘if temperature exceeds 100 degrees then turn off steam supply’. The nature of
the rules is discrete in rule-based control in that the equality being monitored
either has a true or false value, with a definite action as a consequence of the
value of the rule evaluation changing.
Rule-based control is highly suitable where concise rules regarding the
operation of the process can be drawn up. There are many processes where this
is the case and where rule-based control can be successfully applied. For
example, the filling of containers to a minimum weight could employ a concise
rule for the rejection of underweight packages. The rule might take the form: ‘if
the package weight is less than minimum allowable weight, then reject the
package to rework’. Rule-based control does have a place in the operation of
controllers in mills where quality control or operational parameters require
control. For example, the rule might pertain to a limiting ash content or
maximum allowable moisture content in the flour being produced.
Rule-based control schemes are implemented using expert systems or
knowledge-based systems 15 approaches. A number of rule-based packages are
currently available which can be integrated seamlessly with modern Distributed
Control Systems (DCS) or Supervisory Control And Data Acquisition systems
(SCADA). Alternatively rules can be applied using a high-level programming
language.
Fuzzy control is an extension of rule-based control, where the rules are
expressed in a less precise manner. This approach is generally suited to control
problems where smooth changes in the control action are more desirable than
step changes or where it is not possible to define clear boundaries between
process conditions. A typical fuzzy rule might be ‘if the water is hot, and the
house is cold, then the water pump is not running’. It is difficult to see an
application for fuzzy logic in mill direct process control, but the operation of
many of the quality control procedures could potentially benefit from the
application of fuzzy logic. For example ‘hard’ and ‘soft’ wheat, ‘strong’ and
‘weak’ flour are terms in flour mill quality control that are used widely, but
15 An expert or knowledge-based system is a computer program that can capture human expertise,
which can subsequently be applied in a consistent fashion at high speed. The two terms may be used
interchangeably. The object of an expert system in a process scenario would be to monitor process
parameters, give an alarm when a fluctuation occurs and suggest causes and remedies. Taken to its
ultimate and practical limits, such an expert system could actively control plant and tackle process
variations automatically.