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Mathematical Problems in Engineering
Volume 2013, Article ID 531031, 13 pages
Research Article

Artificial Hydrocarbon Networks Fuzzy Inference System

Graduate School of Engineering, Tecnológico de Monterrey, Campus Ciudad de México, 14380 Mexico City, DF, Mexico

Received 13 May 2013; Revised 25 July 2013; Accepted 1 August 2013

Academic Editor: Chen

Copyright © 2013 Hiram Ponce et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper presents a novel fuzzy inference model based on artificial hydrocarbon networks, a computational algorithm for modeling problems based on chemical hydrocarbon compounds. In particular, the proposed fuzzy-molecular inference model (FIM-model) uses molecular units of information to partition the output space in the defuzzification step. Moreover, these molecules are linguistic units that can be partially understandable due to the organized structure of the topology and metadata parameters involved in artificial hydrocarbon networks. In addition, a position controller for a direct current (DC) motor was implemented using the proposed FIM-model in type-1 and type-2 fuzzy inference systems. Experimental results demonstrate that the fuzzy-molecular inference model can be applied as an alternative of type-2 Mamdani’s fuzzy control systems because the set of molecular units can deal with dynamic uncertainties mostly present in real-world control applications.