Particle Swarm Optimization — Based determination of Ziegler-Nichols parameters for PID controller of brushless DC motors

In this article, Ziegler-Nichols and Particle Swarm Optimization algorithms are combined to calculate optimum values for parameters K_P, K_I, K_D in a Proportional-Integral-Derivative controller. We present a novel method searching two-dimensional space instead of three-dimension, so that the calculations of PID parameters become more accurate due to smaller search space. In this research, the efficiency of the combined method in brushless DC motors has been evaluated and the results are presented and compared with the Genetic Algorithm, standard Particle Swarm Algorithm and Advanced Particle Swarm Algorithm. The simulations show that the proposed PID-PSO-ZN algorithm is candidate to be employed in control systems due to its precision to determine optimum PID parameters which reduce the rising time, the settling and overshoot on system response.