this context, FL is a problem-solving control system methodology that lends itself
to implementation in systems ranging from simple, small, embedded micro-controllers
to large, networked, multi-channel PC or workstation-based data acquisition and
control systems. It can be implemented in hardware, software, or a combination
of both. FL provides a simple way to arrive at a definite conclusion based upon
vague, ambiguous, imprecise, noisy, or missing input information.
approach to control problems mimics how a person would make decisions, only much
As the complexity of a system increases, it becomes more difficult
and eventually impossible to make a precise statement about its behavior, eventually
arriving at a point of complexity where the fuzzy logic method born in humans
is the only way to get at the problem.
The concept of Fuzzy Logic (FL)
was conceived by Lotfi Zadeh, a professor at the University of California at Berkley,
and presented not as a control methodology, but as a way of processing data by
allowing partial set membership rather than crisp set membership or non-membership.
This approach to set theory was not applied to control systems until the 70's
due to insufficient small-computer capability prior to that time. Professor Zadeh
reasoned that people do not require precise, numerical information input, and
yet they are capable of highly adaptive control. If feedback controllers could
be programmed to accept noisy, imprecise input, they would be much more effective
and perhaps easier to implement. Unfortunately, U.S. manufacturers have not been
so quick to embrace this technology while the Europeans and Japanese have been
aggressively building real products around it.
is FL different from conventional control methods?
incorporates a simple, rule-based IF X AND Y THEN Z approach to a solving control
problem rather than attempting to model a system mathematically. The FL model
is empirically-based, relying on an operator's experience rather than their technical
understanding of the system. For example, rather than dealing with temperature
control in terms such as "SP =500F", "T <1000F", or "210C
<TEMP <220C", terms like "IF (process is too cool) AND (process
is getting colder) THEN (add heat to the process)" or "IF (process is
too hot) AND (process is heating rapidly) THEN (cool the process quickly)"
are used. These terms are imprecise and yet very descriptive of what must actually
happen. Consider what you do in the shower if the temperature is too cold: you
will make the water comfortable very quickly with little trouble. FL is capable
of mimicking this type of behavior but at very high rate.
does Fl work?
requires some numerical parameters in order to operate such as what is considered
significant error and significant rate-of-change-of-error, but exact values of
these numbers are usually not critical unless very responsive performance is required
in which case empirical tuning would determine them. For example, a simple temperature
control system could use a single temperature feedback sensor whose data is subtracted
from the command signal to compute "error" and then time-differentiated
to yield the error slope or rate-of-change-of-error, hereafter called "error-dot".
Error might have units of degs F and a small error considered to be 2F while a
large error is 5F. The "error-dot" might then have units of degs/min
with a small error-dot being 5F/min and a large one being 15F/min. These values
don't have to be symmetrical and can be "tweaked" once the system is
operating in order to optimize performance. Generally, FL is so forgiving that
the system will probably work the first time without any tweaking.
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