Fuzzy Vs. neuro-fuzzy: Implementation on the reconfigurable FPGA system

Fuzzy logic based inference techniques provide efficient solution for control problems in engineering applications. However due to lack of systematic approaches for hardware implementation of complex fuzzy controllers limits the applicability of these techniques in modern industrial applications. This paper, aims to address various hardware implementation issues of fuzzy system on a reconfigurable FPGA platform. It also proposes hardware friendly neuro-fuzzy technique as a better alternation of a fuzzy system. A simple problem has been realization on the Xilinx SPARTAN 3AN FPGA development board to demonstrate the feasibility and superiority of the neuro-fuzzy over the fuzzy system. The results obtained under this study clearly show that neuro-fuzzy technique is the optimum choice in terms of speed, accuracy and resource utilization if hardware implementation is concerned.