Novel genetic optimization of membership functions of fuzzy logic for speed control of a direct current motor for hardware applications in FPGAs

• Autorzy: Maldonado Y. , Castillo O. , Melin P.
• Języki publikacji: EN

Abstrakty

EN

This paper proposes a novel method for genetic optimi zation of triangular and trapezoidal membership functions of fuzzy systems, for hardware applications such as the FPGA (Field Programmable Gate Array). This method con sists in taking only certain points of the membership func tions, with the purpose of giving more efficiency to the algorithm. The genetic algorithm was tested in a fuzzy con troller to regulate engine speed of a direct current (DC) motor, using the Xilinx System Generator (XSG) toolbox of Matlab, which simulate VHDL (Very High Description Lang uage) code.

Słowa kluczowe

EN

genetic algorithms; fuzzy; controller; MATLAB; Simulink; Xilinx system generator; VHDL; FPGA

• Wydawca: Łukasiewicz Industrial Research Institute for Automation and Measurements PIAP
• Czasopismo: Journal of Automation Mobile Robotics and Intelligent Systems
• Rocznik: 2010
• Tom: Vol. 4, No. 4
• Strony: 53--63
• Opis fizyczny: Bibliogr. 28 poz., rys.

Twórcy

autor

Maldonado Y.

autor

Castillo O.

autor

Melin P.

• Tijuana Institute of Technology, Tijuana, Mexico.,

Bibliografia

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