A cultural algorithm based particle swarm optimization approach to linear brushless DC motor PID controller

This paper presents a new hybrid Cultural Algorithm (CA) based particle swarm optimization (PSO) that converges to a significantly more accurate solution then existing particle swarm optimization and which has also been applied to the linear brushless DC motor PID controller design. The utility of hybrid CA based PSO is demonstrated by determining the optimal proportional-integral-derivative (PID) controller parameters for speed control of a linear brushless DC motor and then compared with basic PSO method. The proposed hybrid approach has superior 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 comparative experimental results has demonstrated the feasibility and effectiveness of the proposed novel approach.