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--Permanent magnet Brushless DC Motor has been commonly utilized in fields that necessitate high fidelity and specific control, owing to its simple structure, high power density, high efficiency, high starting torque, long operating life, and prolonged ranges of speed. While considering of the drive part of the motor, the most significant part is commutation control. During commutation, they generate some high torque ripples which are caused by non-ideal commutation currents in the stator windings which confines its application, exclusively at low-voltage fields. In this paper we compare the efficiency of conventional and artificial intelligence in torque controlling of permanent magnet brushless DC motor. It presents the study, analysis and comparison of the PI controller, Genetic Algorithm, Artificial Neural Network and Fuzzy Logic Controller. Disadvantages of PI controller can be overcome further by the advanced genetic algorithm based controller. This system has adaptive voltage reference and controls its speed. But its settling time is more. Thus the disadvantage of genetic algorithm based controller can be overcome further by the artificial neural controller. It has excellent flexibility and adaptability as well as high precision and good robustness is obtained. But it’s settling time is also larger. Thus the disadvantage of the three controllers can be overcome further by Fuzzy Logic Controller and it has settling time of torque is too small. So it is observed that Fuzzy Logic based controller give better response than other controllers for the torque control DC

Extensive Survay on Torque Controlling of PMBLDC- Motor using Conventional Artificial Intelligent Controllers