Optimal Tuning of PID Controller for a Linear Brushless DC Motor using Particle Swarm Optimization Technique

This Paper presents a novel Cultural Algorithm based particle swarm optimization (PSO) technique which is intended to assist in converging to a accurate solution in the control of Linear Brushless Direct Current motor (LBLDC). With the novel PSO-based approach the optimal Proportional-Integral-Derivative (PID) controller parameters are deduced for efficient speed control of Linear Brushless DC motor. In the present paper, an modern heuristic algorithm based on the behavior of organisms, such as bird schooling has been implemented in MATLAB and Linear Brushless DC motor modeled in Simulink. The proposed approach has efficient features including stable convergence characteristic and good computational efficiency, reducing the steady-state error (Ess), rise time (Tr), settling time (Ts) and maximum overshoot (Mp) in speed control of a Linear Brushless DC motor. The experimental results implicate the effectiveness of the approach. Keywords--Proportional-Integral-Derivative Controller, Cultural Algorithm, Particle Swarm Optimization, Linear Brushless DC motor.