Abstract:
For improving the speed and torque of the BLDC motor is applied an improved method is based Direct Torque Control (DTC) technique. Gravitational Search Algorithm (GSA) and the Radial Basis Function Neural Network (RBFNN) method are equated in an improved method. By updating the randomized stricture, the updating performance of the GSA is showed. The RBFNN is used for developed the execution of the GSA and modernizing the stricture. The huge torque ripple in commutation part found once the DTC approach is worked in the conduction mode. FOPID is improved as the speed and torque control of BLDC motor. In conclusion, the proposed method is applied in the MATLAB/Simulink platform. The functional maximized of the suggested technique is recognized and combined with the modern strategies such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO)-RBFNN procedures.
