Optimal design of type-2 fuzzy controllers with a multiple objective genetic algorithm for FPGA implementation

This paper describes the design and testing of the optimal type-2 fuzzy controller obtained using genetic algorithms (GA) for the optimization of triangular and trapezoidal membership functions of a fuzzy system, for hardware representations such as the Field Programmable Gate Array (FPGA). The GA uses only certain points of the membership functions, the fuzzy rules are not changed, with the purpose of giving more efficiency to the algorithm. The GA was tested in a type-2 fuzzy logic controller (FLC) to regulate the direct current (DC) motor speed, using the Matlab-Simulink programming language and VHDL (Very High Description Language) code. Comparisons were made between the type-1 FLC versus type-2 FLC, to evaluate the difference in performance of both types of controllers.