During the past few years two principally different approaches to
the design of fuzzy controllers have emerged: heuristics-based
design and model-based design. The main motivation for the
heuristics-based design is given by the fact that many industrial
processes are still controlled in one of the following two ways: -
The process is controlled manually by an experienced operator. -
The process is controlled by an automatic control system which
needs manual, on-line 'trimming' of its parameters by an
experienced operator. In both cases it is enough to translate in
terms of a set of fuzzy if-then rules the operator's manual control
algorithm or manual on-line 'trimming' strategy in order to obtain
an equally good, or even better, wholly automatic fuzzy control
system. This implies that the design of a fuzzy controller can only
be done after a manual control algorithm or trimming strategy
exists. It is admitted in the literature on fuzzy control that the
heuristics-based approach to the design of fuzzy controllers is
very difficult to apply to multiple-inputjmultiple-output control
problems which represent the largest part of challenging industrial
process control applications. Furthermore, the heuristics-based
design lacks systematic and formally verifiable tuning tech niques.
Also, studies of the stability, performance, and robustness of a
closed loop system incorporating a heuristics-based fuzzy
controller can only be done via extensive simulations."
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