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Fuzzy logic in control
This activity is aimed to investigate the application of the fuzzy logic
paradigm for the control and indentification of dynamic system. In particular,
fuzzy logic in control has been successfully used to capture heuristic
control laws obtained from human experience or engineering practice in
automated algorithm. These control laws are defined by means of linguistic
rule, for example "if the pressure is high, then decrease the pump power".
The heuristic approach in the controller design can be appealing for its
simplicity, but formal design method can be mandatory in some cases. For
this reason a great endeavor is carrying out by several researcher in defining
formal design procedures.
Fuzzy model identification
In literature a general approach to nonlinear structure modeling does not exist and then fuzzy models are interesting because they can approximate a large class of nonlinear functions. The maim problem consists in finding the parameters of the fuzzy model from data affected by noise. A well-established procedure, the Frisch Scheme, for linear identification in stochastic environment has been modified and exploited to be applied to fuzzy model identification. The extension of the implemented technique for the identification of multidimensional piece-wise linear causal models and piece-wise linear fuzzy models allows to identify nonlinear dynamic models.
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