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This paper presents nature-inspired optimization algorithms such as particle swarm optimization (PSO) algorithm and bat algorithm (BA) for tuning PID controller parameters of BLDC motor drive. Both PSO algorithm BA are population based algorithms. Population based algorithms have number of advantages over classical methods for solving complex optimization problems. The position of BLDC rotor is determined by measuring the changes in the Back emf. Sensorless control method reduces the cost of motor as it does not need sensors for the detection of rotor position. The BLDC motor drive is modelled in Matlab/simullink. The simulation results reveals that proposed methods are effective in reducing the time domain parameters steady state error, rise time, settling time and peak overshoot.

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