Open AccessAdaptive Neuro Fuzzy Technique for Speed Control of Six-Step Brushless DC Motor
Author(s) -
H. Abdelfattah
Publication year - 2021
Publication title -
international journal of energy
Language(s) - English
Resource type - Journals
ISSN - 1998-4316
DOI - 10.46300/91010.2021.15.10
Subject(s) - dc motor , matlab , adaptive neuro fuzzy inference system , robustness (evolution) , control theory (sociology) , electronic speed control , computer science , inverter , control engineering , fuzzy logic , voltage , fuzzy control system , engineering , artificial intelligence , control (management) , electrical engineering , biochemistry , chemistry , gene , operating system
The brushless DC motors with permanent magnets (PM-BLDC) are widely used in a miscellaneous of industrial applications. In this paper, The adaptive neuro fuzzy inference system (ANFIS) controller for Six-Step Brushless DC Motor Drive is introduced. The brushless DC motor’s dynamic characteristics such as torque , current , speed, , and inverter component voltages are showed and analysed using MATLAB simulation. The propotional-integral (PI) and fuzzy system controllers are developed., based on designer’s test and error process and experts. The experimential and hardware resuts for the inverter- driver circuits are presented. The simulation results using MATLAB simulink are conducted to validate the proposed (ANFIS) controller’s robustness and high performance relative to other controllers.