The research interest of Oscar Cordón are:

• Combination of Fuzzy Logic and Genetic Algorithms
• Fuzzy Logic Controllers

Combination of Fuzzy Logic and Genetic Algorithms

UP

The connection between fuzzy logic and genetic algorithms is bidirectional. In one direction, genetic algorithms are utilized to deal with various optimization problems involving fuzzy systems. In the other direction, different fuzzy logic based techniques may be used for trying to improve the genetic algorithms behaviour: fuzzy logic control systems for designing self-control processes according to some performance measures, fuzzy operators, etc, thus, classical genetic algorithms can be fuzzified, the resulting are called fuzzy genetic algorithms.

The results achieved concern:

• Fuzzy Genetic Algorithms
  • Analysis of the real coded representation.
  • Crossover operator definition using fuzzy connectives; for designing crossover operators that establish adequate population diversity levels and so attacking the premature convergence as well.
  • Dynamic and Heuristic Crossover Operators.

• Genetic Fuzzy Systems: Fuzzy Control
  • Tuning fuzzy logic controllers.
  • Learning processes of fuzzy control rules.

• Genetic Algorithms and Fuzzy Optimization
  • Application of the Genetic Algorithms to Fuzzy Optimization Problems.

• Combination Fuzzy Logic-Genetic Algorithms Bibliography

Fuzzy Logic Controllers

UP

Fuzzy logic controllers (FLC) are rule based systems which have an effective utilization in the context of complex ill-defined processes, especially those which can be controlled by a skilled human operator without the knowledge of their underlying dynamics. The essential part of the FLC system is a set of fuzzy control rules (FCR) related by means of a fuzzy implication and the compositional rule of inference. FCR are usually formulated in linguistic terms, in the form of "IF THEN" rules, and there are different modes to derive them. Recently fuzzy control techniques have been applied to many industrial processes.

The results achieved concern:

• Applicability of the Fuzzy Operators in the Design of Fuzzy Logic Controllers.
  • Influence of the fuzzy implication functions and defuzzification methods.
  • The use of T-Norms.
  • Analysis of the implication operators.

• Learning of fuzzy control rules using genetic algorithms.

See related publications