A fuzzy logic application for selecting layered manufacturing techniques

“…For triangular MFs, only the peaks of the triangles which construct the rule base take part in the crossover process. Suppose the two triangles which take part in crossover have the base points given by [a 1 …”

Section: A Genetic Algorithm For Tuning Of the Rule Basementioning

confidence: 99%

“…Fuzzy logic controllers (FLC) have immensely contributed to the industrial sector [1][2][3][4]. They have been of greater use to solve complex and non-linear control problems.…”

Section: Introductionmentioning

confidence: 99%

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FPGA implementation of rule optimization for stand-alone tunable fuzzy logic controller using GA

Jammu

Pati

Patra

et al. 2016

Complex Intell. Syst.

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In this paper, self-tuned, rule-optimized multiinput and multi-output (MIMO) fuzzy logic controller (FLC) is implemented on field programmable gate arrays (FPGA). The design of membership functions, rule base are made with aid of genetic algorithm (GA). Flexibility in FPGA design is implemented through tuning of FLC parameters. The system is modularized as rule base development, rule base transfer and computations on FPGA. Based on the system, an experimental dataset is obtained, which is utilized in a capable computing platform so as to develop a fine-tuned fuzzy rule base. The synthesized rule base is transferred to FPGA along with user provided inputs through a GUI. The GUI also displays the output result sent by FPGA. The communication between the GUI and the FPGA is done via universal asynchronous receiver and transmitter. Rule-optimized FLC is implemented on Xilinx Virtex-5 LX110T board. This dedicated single chip architecture performs high-speed fuzzy inferences with processing speed up to 760 KFLIPS at a clock frequency of 247 MHz using 8 rules, 2 input variables at 16-bit resolution. Experiments of software implementation and hard-

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“…In most applications, an FL solution is a translation of a human solution. Thirdly, FL can model nonlinear functions of arbitrary complexity to a desired degree of accuracy (Samir Khrais, et al, 2011). FL is a convenient way to map an input space to an output space.…”

Section: Fuzzy Logicmentioning

confidence: 99%

Customized Modeling and Manufacturing of Cranioplastic Implant using Rapid Prototyping

ogeswaran¹

2010

Int.J.of Curr. Engg. and Technol

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A fuzzy logic application for selecting layered manufacturing techniques

Cited by 34 publications

References 20 publications

Fuzzy Multi-actor Multi-criteria Decision Making for sustainability assessment of biomass-based technologies for hydrogen production

Fuzzy Multi-actor Multi-criteria Decision Making for sustainability assessment of biomass-based technologies for hydrogen production

FPGA implementation of rule optimization for stand-alone tunable fuzzy logic controller using GA

Customized Modeling and Manufacturing of Cranioplastic Implant using Rapid Prototyping

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