Abstract
In this paper a method to design modular type-1 fuzzy controllers using genetic optimization is presented. The method is tested with a problem that requires five individual controllers. Simulation results with a genetic algorithm for optimizing the membership functions of the five individual controllers are presented. Simulation results show that the proposed modular control approach offers advantages over existing control methods.
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Cervantes, L., Castillo, O. (2013). Genetic Optimization of Modular Type-1 Fuzzy Controllers for Complex Control Problems. In: Melin, P., Castillo, O. (eds) Soft Computing Applications in Optimization, Control, and Recognition. Studies in Fuzziness and Soft Computing, vol 294. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35323-9_6
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DOI: https://doi.org/10.1007/978-3-642-35323-9_6
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