Rockwell Automation RSLogix 5000 Fuzzy Designer - Manual (Page 13)

Publication LOGIX-UM004A-EN-P - March 2007
Get Started with FuzzyDesigner 13
An expert may be an operator, a maintenance person, or a control
engineer, who knows what adjustments are needed during process
instability. These adjustments may include defining setpoints for
process variables, defining control action in feedforward or feedback
contro,l or setting gains of conventional controllers, and may be as
simple as turning a valve or knob.
Rockwell Automation is introducing a tool for building smart
instructions that encode If-Then rules and use fuzzy logic internally to
describe vague and incomplete knowledge in a natural way. Fuzzy
Logic may serve in situations where:
• the process has not been automated and is running in Manual
mode.
• a well-tuned PID controller does not provide the desired
response, however, the expert knowledge is available to define
the rules for a fuzzy algorithm.
Let’s look at an example where we will discuss building a Heat,
Ventilation and Air Conditioning (HVAC) system that manipulates the
compressor speed based on room temperature and humidity. In HVAC
systems, room comfort is often associated with vague (fuzzy) values of
temperature and humidity that are more suitable for describing the
problem than numerical (crisp) values.
Fuzzy rules used in this example might be as follows.
Consider these factors when developing fuzzy rules:
• How do I specify High and other fuzzy values in fuzzy rules?
• How do the rules process numerical inputs provided by tags
associated with sensors?
• How do the rules derive outputs from inputs?
• If the output generated is vague (fuzzy), how do I get the
numerical (crisp) value at the output when needed?
If Then
Temperature is high and humidity is
high Speed is medium
Temperature is medium and humidity
is very high Speed is high