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Article type: Research Article
Authors: Souza, Gabriel A.F.a | Santos, Rodrigo B.a | Rocha Rizol, Paloma M.S.b | Oliveira, Duarte L.a | Faria, Lester A.a; *
Affiliations: [a] Departamento de Eletrônica Aplicada, Instituto Tecnológico de Aeronáutica, Praça Marechal Eduardo Gomes 50, CEP12228-900, São José dos Campos, SP, Brazil | [b] Departamento de Engenharia Elétrica, UNESP - Universidade Estadual Paulista, campus de Guaratinguetá, Avenida Ariberto Pereira da Cunha, CEP12516-410, Guaratinguetá, SP, Brazil
Correspondence: [*] Corresponding author. Lester A. Faria, Departamento de Eletrônica Aplicada, Instituto Tecnológico de Aeronáutica, Praça Marechal Eduardo Gomes 50, CEP12228-900, São José dos Campos, SP, Brazil. E-mail: lester@ita.br.
Abstract: A novel analog fuzzy membership function generator architecture, based on current steering mirrors, for interval type-2 fuzzy controllers is proposed in this paper. The Footprint of Uncertainty (FOU), characteristic of an interval type-2 fuzzy set, is generated by this novel architecture, which uses current steering mirrors controlled by a voltage input and allows width variation based on a central line. This main feature makes the circuit inherently type-2, i.e., not dependent of any type-1 fuzzifier, unlike all previous analog fuzzifiers found in the literature. The circuit operates in current mode and is capable of generating trapezoidal, triangular, Z-shaped and S-shaped membership functions. Input currents allow shape configuration, whereas a digitally programmable current mirror provides different inclinations, making it fully programmable (shape, width of the FOU, inclination, and position). Simulations validating the architecture were performed with TSMC CMOS 0.18μm technology, in CADENCE software. The circuit was later fabricated and characterized. Experimental results confirmed its ability to work as a fuzzifier, with all specified features, showing to be suitable even for dedicated low power applications.
Keywords: Analog circuits, low-power, fuzzifier, interval type-2 fuzzy logic
DOI: 10.3233/JIFS-171118
Journal: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 1, pp. 203-212, 2018
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