z-logo
open-access-imgOpen Access
FPGA Realization of ANFIS Controller Using a Proposed Digital Design
Author(s) -
Abbas H. Issa,
Sabah A. Gitaffa,
Abdulrahim Thiab Humod
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1973/1/012019
Subject(s) - vhdl , field programmable gate array , adaptive neuro fuzzy inference system , computer science , embedded system , controller (irrigation) , computer hardware , matlab , realization (probability) , robustness (evolution) , control engineering , fuzzy logic , engineering , fuzzy control system , artificial intelligence , operating system , mathematics , biochemistry , statistics , chemistry , gene , agronomy , biology
The design and realization of Adaptive Neuro-Fuzzy Inference System (ANFIS) controller based on Field Programmable Gate Array (FPGA) is presented in this paper. The controller intended to control the temperature of medical oven. A novel design of digital ANFIS is presented here for the implementation process. Different controllers are designed and their results are compared using MATLAB program to show the ANFIS superiority. The designed controllers tested for cell cultures application at 37.5. A reduction is made for the designed digital ANFIS due to the used FPGA limitations. The reduced design minimizes the utilized slices from 366% to 3% and LUTs from 364% to 3%. The reduced design reached an optimum size for this controller to utilize a smallest memory size. A real-time FPGA implementation of the proposed digital ANFIS have been done and verified through Xilinx ISE 14.6 using the VHDL language. The VHDL code for the controller is produced, aggregated and downloaded on the FPGA Spartan 3A/AN FPGA kit. A comparison between the simulation and implementation results is made. The matching between these results proves the effectiveness and robustness of the proposed digital ANFIS and the excellent performance of the FPGA based controller.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here