A new improved algorithm for speed control of Brushless DC motor

In this work, a new hybrid algorithm has been developed by combining Particle Swarm Optimization (PSO) and Differential Evolution (DE) algorithms to obtain efficient speed control of Brushless Direct Current (BLDC) motor under various conditions. The results obtained are compared with those obtained using Fuzzy Logic Controller, Fuzzy Proportional Integral (PI) Controller and Particle Swarm Optimization (PSO) based Fuzzy PI Controller which have been developed for the same application, under the same conditions. The performance of all the controllers are analyzed under the operating conditions of, varying speed no load, varying speed at constant load, varying load at constant speed and varying speed and load simultaneously. The above-mentioned four algorithms have been developed and implemented in Matlab/ Simulink environment and it has been found that the speed regulation by the proposed hybrid PSODE-Fuzzy PI controller is well above the rated values.