This paper proposes a design of multi-objective genetic optimization for the average approximation of an interval type-2 fuzzy logic controller (AT2-FLC) using linear combination of individual criteria. There has been shown, on the real case, that the proposed method can be competitive to other commonly used approaches in the design of fuzzy controllers. The AT2-FLC was tested with different levels of uncertainty and different number of bits for the VHDL codification to regulate speed in a direct current motor (ReSDCM). Comparisons were made between the type-1 fuzzy logic controller versus AT2-FLC synthesized in VHDL code for FPGA and the AT2-FLC in VHDL versus the PID controller to ReSDCM. The main contribution of the paper is the design, implementation and comparison of multi-objective GA optimization of AT2-FLC for FPGA real applications. The AT2-FLC is targeted to a Xilinx Spartan 3A XC3S700A device using the Xilinx Foundation Environment. 
A multi-objective optimization of type-2 fuzzy control speed in FPGAs