Modeling, simulation and performance analysis of the three phase permanent magnet brushless direct current (pmbldc) motor using neuro-fuzzy controllerbased genetic algorithm

In this paper, modeling, simulation and performance analysis of the three phase permanent magnet brushless direct current (PMBLDC) motor using Fuzzy Logic Controller (FLC), hybrid Fuzzy-Genetic Algorithm controller (FGAC), hybrid Neuro-Genetic Algorithm Controller (NGAC), Hybrid Neuro-Fuzzy controller (NFC) and Hybrid Neuro-Fuzzy controller (NFC) based on Genetic Algorithm (GA) under the effect of external load for improving the transient and steady state response is presented. The applications of the three phase permanent magnet brushless direct current (PMBLDC) motor are increasing day by day. In order to have proper utilization of these motors and to control them effectively it is important to have proper mathematical modeling of these motors. Similarly effective control these motors are also essential to have successful application of the devices across multiple domains. This paper handles both these important aspects. A mathematical model has been derived to represent a three phase permanent magnet brushless direct current (PMBLDC) motor model, its utility can be noted from the fact that different motors can be analyzed easily using the proposed model. The mathematical model was subjected to open loop and closed loop analysis to study the stability and performance. In this paper in order to validate the approach a MATLAB/SIMULINK model having intelligent controllers are constructed to control the modeled three phase permanent magnet brushless direct current (PMBLDC) motor under the effect of external disturbances for enhancement of static & dynamic response.