FPGA-Based Implementation of Genetically Tuned Fuzzy Logic Controller (GA-FLC)

A. Hussein, Emad; G. Samir, Ammar

	FPGA-Based Implementation of Genetically Tuned Fuzzy Logic Controller (GA-FLC)
Journal of Engineering and Sustainable Development
Article 1, Volume 16, Issue 3, 2012, Pages 241-257
Authors
Emad A. Hussein; Ammar G. Samir
Abstract
Fuzzy Logic controller (FLC) contains three operations; the fuzzification of the inputs, the knowledge base (data base and rule base), and the defuzzification of the output. In this paper our fuzzy controller contains two inputs and one output each have five membership functions. This fuzzy controller will pass through two operations; the first is to tune the input/output scaling factor (SF) and the second operation is to tune the membership function parameters. This tuning is done by the use of Genetic Algorithm (GA). The tuned fuzzy controller then will be reduced to a look-up table by taking the whole fuzzy probabilities. The output for the tuned fuzzy controller will be obtained using center of gravity method. To apply this tuned circuit we must translate the resulted table to digital binary values using a special encoder then to a set of boolean functions. Finally FPGA technology will be used to describe the resulted boolean functions by the use of the FPGA programming language (VHDL) hardware description language. The output will then pass through the decoder to get the suitable control action. The most important advantage of our method is to describe the FLC using digital numbering system applied to FPGA technology to achieve high processing speed for the fuzzified output per second and also the speed of this controller is independent of the number of fuzzy rules.
Keywords
Fuzzy Logic Controller; genetic algorithm; FPGA and VHDL

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