Abstract
This paper proposes the particle swarm optimization (PSO) of type-2 membership functions for average approximation of an interval type-2 fuzzy logic system (AT2-FIS), the AT2-FIS is synthesized in VHDL code for FPGAs. The PSO method considers three objective functions, overshoot, undershoot and steady state error because the real application is to control the speed of a DC motor. Several experiments were performed to optimize the AT2-FIS in FPGA. Experiments were conducted by changing the number of bits for encoding the AT2-FLC in VHDL.
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Maldonado, Y., Castillo, O., Melin, P. (2013). Particle Swarm Optimization for Average Approximation of Interval Type-2 Fuzzy Inference Systems Design in FPGAs for Real Applications. In: Castillo, O., Melin, P., Kacprzyk, J. (eds) Recent Advances on Hybrid Intelligent Systems. Studies in Computational Intelligence, vol 451. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33021-6_3
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DOI: https://doi.org/10.1007/978-3-642-33021-6_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33020-9
Online ISBN: 978-3-642-33021-6
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