The control strategy used by the human being can be
represented by conditional fuzzy relations (Zhang &
Litchfield, 1993), which form a group of decisionmaking
rules of similar formalism to represent knowledge
and infer new knowledge. The fuzzy control
systems have come into prominence due to their applicable
approach, attractive for complex processes, their
characteristic action based on knowledge of the system
and on qualitative dynamic behavior, and, when measurements
are uncertain, incorporating the non-linearity
into the methodology of the project. This methodology
involves rules formulation, logical operators and membership
functions, which map the input and output variables
by an inference process (Arbex, 1994).
The control strategy used by the human being can be
represented by conditional fuzzy relations (Zhang &
Litchfield, 1993), which form a group of decisionmaking
rules of similar formalism to represent knowledge
and infer new knowledge. The fuzzy control
systems have come into prominence due to their applicable
approach, attractive for complex processes, their
characteristic action based on knowledge of the system
and on qualitative dynamic behavior, and, when measurements
are uncertain, incorporating the non-linearity
into the methodology of the project. This methodology
involves rules formulation, logical operators and membership
functions, which map the input and output variables
by an inference process (Arbex, 1994).
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