Automatic Estimation of the Fusion Method Parameters to Reduce Rule Base of Fuzzy Control Complex Systems

  • Yulia Nikolaevna Ledeneva
  • Carlos Alberto Reyes García
  • José Antonio Calderón Martínez
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4293)


The application of fuzzy control to large-scale complex systems is not a trivial task. For such systems the number of the fuzzy IF-THEN rules exponentially explodes. If we have l possible linguistic properties for each of n variables, with which we will have l n possible combinations of input values. Large-scale systems require special approaches for modeling and control. In our work the sensory fusion method is studied in an attempt to reduce the size of the inference engine for large-scale systems. This method reduces the number of rules considerably. But, in order to do so, the adequate parameters should be estimated, which, in the traditional way, depends on the experience and knowledge of a skilled operator. In this work, we are proposing a method to automatically estimate the corresponding parameters for the sensory fusion rule base reduction method to be applied to fuzzy control complex systems. In our approach, the parameters of the sensory fusion method are found through the use of genetic algorithms. The implementation process, the simulation experiments, as well as some results are described in the paper.


Fuzzy System Fuzzy Rule Rule Base Fuzzy Control Fuzzy Controller 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Yulia Nikolaevna Ledeneva
    • 1
  • Carlos Alberto Reyes García
    • 1
  • José Antonio Calderón Martínez
    • 2
  1. 1.National Institute of Astrophysics, Optics and Electronics 
  2. 2.Technological Institute of Aguascalientes 

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