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

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.

Keywords

• Fuzzy Logic Controller
• FLC
• Genetic Algorithm
• GA
• FPGA and VHDL